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+++ b/publications.html
@@ -54,598 +54,375 @@ <h1 class="display-4">Publications</h1>
                     <ul class="list-pointer list-pointer-sm list-pointer-primary">
                         <li>Bea, Y., Jiménez, R., Mateos, D., Liu, S., Protopapas, P., Tarancón-Álvarez, P., Tejerina-Pérez, P. 
                             "Gravitational duals from equations of state." Journal of High Energy Physics, 2024(7), 87 (2024).</li>
-                        
+                         
                         <li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin. 
-                            "IoT Malware Data Augmentation using a Generative Adversarial Network." HICSS 2024: 7572-7581  (2024).</li>
-                        
+​                            "IoT Malware Data Augmentation using a Generative Adversarial Network." HICSS 2024: 7572-7581  (2024).</li>
+                                 
                         <li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin. 
-                            "Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings." 
-                            HICSS 2024: 7582-7591 (2024).</li>
-                        
+​                            "Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings." 
+​                            HICSS 2024: 7582-7591 (2024).</li>
+                         
                         <li>A.T. Chantada, S.J. Landau, P. Protopapas, C.G. Scóccola, C. Garraffo. 
-                            "Faster Bayesian inference with neural network bundles and new results for ΛCDM models." 
-                            Physical Review D 109 (12), 123514 (2024).</li>
+​                            "Faster Bayesian inference with neural network bundles and new results for ΛCDM models." 
+​                            Physical Review D 109 (12), 123514 (2024).</li>
                         
                         <li>V.S. Pérez Díaz, J. Ingram, V. Kashyap, J. Martinez Galarza, P. Protopapas. 
-                            "Enhancing Chandra-Gaia Crossmatching with Machine Learning." 
-                            AAS/High Energy Astrophysics Division 21, 105.02 (2024).</li>
-                        
+​                            "Enhancing Chandra-Gaia Crossmatching with Machine Learning." 
+​                            AAS/High Energy Astrophysics Division 21, 105.02 (2024).</li>
+                         
                         <li>A. Mohan, P. Protopapas, K. Kunnumkai, C. Garraffo, L. Blackburn, et al. 
-                            "Generating images of the M87* black hole using GANs." Monthly Notices of the Royal Astronomical Society 527 (4),
-                             10965-10974 (2024).</li>
-                        
+​                            "Generating images of the M87* black hole using GANs." Monthly Notices of the Royal Astronomical Society 527 (4),
+​                             10965-10974 (2024).</li>
+                       
                         <li>M. Cresitello-Dittmar, J. McDowell, D. Tody, T. Budavari, M. Dolensky, et al.
-                             "IVOA Spectrum Data Model Version 1.2." IVOA Recommendation 15 December 2023.</li>
+​                             "IVOA Spectrum Data Model Version 1.2." IVOA Recommendation 15 December 2023.</li>
                         
                         <li>A.T. Chantada, S.J. Landau, P. Protopapas, C.G. Scóccola, C. Garraffo. 
-                            "NN bundle method applied to cosmology: an improvement in computational times."
-                             arXiv preprint arXiv:2311.15955 (2023).</li>
+​                            "NN bundle method applied to cosmology: an improvement in computational times."
+​                             arXiv preprint arXiv:2311.15955 (2023).</li>
                         
                         <li>W. Lei, P. Protopapas, J. Parikh. "One-Shot Transfer Learning for Nonlinear ODEs." 
-                            arXiv preprint arXiv:2311.14931 (2023).</li>
-                        
+​                            arXiv preprint arXiv:2311.14931 (2023).</li>
                         <li>D. Moreno-Cartagena, G. Cabrera-Vives, P. Protopapas, C. Donoso-Oliva, et al. 
-                            "Positional Encodings for Light Curve Transformers: Playing with Positions and Attention." 
-                            arXiv preprint arXiv:2308.06404 (2023).</li>
-                        
-                        <li>K. Ly, J. Kurlander, M. Holman, M. Payne, A. Heinze, P. Bernardinelli, et al. "2010 RJ226." Minor Planet Electronic Circulars 2023.</li>
-                        
-                        <li>J. Carter, S. Mancoridis, P. Protopapas. "Optimal data sample length for system call traces for malware detection in an iot ecosystem." 2023 3rd International Conference on Electrical, Computer, Communications and Electronics Engineering.</li>
-                        
-                        <li>S. Liu, X. Huang, P. Protopapas. "Residual-based error bound for physics-informed neural networks." Uncertainty in Artificial Intelligence, 1284-1293 (2023).</li>
-                        
-                        <li>A.T. Chantada, S.J. Landau, P. Protopapas, C.G. Scóccola, C. Garraffo. "Cosmology-informed neural networks to solve the background dynamics of the Universe." Physical Review D 107 (6), 063523 (2023).</li>
-                        
-                        <li>M. Mattheakis, H. Joy, P. Protopapas. "Reservoir Computing for Solving Ordinary Differential Equations." International Journal on Artificial Intelligence Tools 32 (01), 2350030 (2023).</li>
-                        
-                        <li>J. Astudillo, P. Protopapas, K. Pichara, I. Becker. "A Reinforcement Learning–Based Follow-up Framework." The Astronomical Journal 165 (3), 118 (2023).</li>
-                        
-                        <li>C. Donoso-Oliva, I. Becker, P. Protopapas, G. Cabrera-Vives, M. Vishnu, et al. "ASTROMER-A transformer-based embedding for the representation of light curves." Astronomy & Astrophysics 670, A54 (2023).</li>
-                        
-                        <li>T. Allen, F. Grezes, G. Shapurian, S. Blanco-Cuaresma, C. Grant, et al. "ADS Machine Learning and Deep Learning Efforts." American Astronomical Society Meeting Abstracts 55 (2), 177.37 (2023).</li>
-                        
-                        <li>T.A.E. Ferreira, M. Mattheakis, P. Protopapas. "A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function." arXiv:2101.06100 (2021).</li>
-                        
-                        <li>D. Sondak, P. Protopapas. "Learning a Reduced Basis of Dynamical Systems using an Autoencoder." arXiv:2011.07346 (2020).</li>
-                        
-                        <li>R. Fang, D. Sondak, P. Protopapas, S. Succi. "Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow." Journal of Turbulence 21(9-10), 525-543 (2020).</li>
-                        
-                        <li>L. Zorich, K. Pichara, P. Protopapas. "Streaming classification of variable stars." Monthly Notices of the Royal Astronomical Society 492(2), 2897-2909 (2020).</li>
-                        
-                        <li>C. Flamant, P. Protopapas, D. Sondak. "Solving Differential Equations Using Neural Network Solution Bundles." arXiv preprint arXiv:2006.14372 (2020).</li>
-                        
-                        <li>F. Chen, D. Sondak, P. Protopapas, M. Mattheakis, S. Liu, D. Agarwal, M. Di Giovanni. "NeuroDiffEq: A Python package for solving differential equations with neural networks." Journal of Open Source Software 5(46), 1931 (2020).</li>
-                        
-                        <li>N. Astorga, P. Huijse, P. Protopapas, P. Estévez. "Matching Priors and Conditionals for Clustering." European Conference on Computer Vision, 658-677 (2020).</li>
-                        
-                        <li>W. Wu, P. Protopapas, Z. Yang, P. Michalatos. "Gender classification and bias mitigation in facial images." 12th ACM Conference on Web Science, 106-114 (2020).</li>
-                        
-                        <li>H. Jin, M. Mattheakis, P. Protopapas. "Unsupervised Neural Networks for Quantum Eigenvalue Problems." arXiv:2010.05075 (2020).</li>
-                        
-                        <li>M. Mattheakis, D. Sondak, A.S. Dogra, P. Protopapas. "Hamiltonian Neural Networks for solving differential equations." arXiv:2001.11107 (2020).</li>
-                        
-                        <li>A. Paticchio, T. Scarlatti, M. Mattheakis, P. Protopapas, M. Brambilla. "Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread." arXiv e-prints: 2020arXiv201005074P (2020).</li>
-                        
-                        <li>D. Randle, P. Protopapas, D. Sondak. "Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks." arXiv preprint arXiv:2007.11133 (2020).</li>
-                        
-                        <li>R. Carrasco-Davis, G. Cabrera-Vives, F. Förster, P.A. Estevez, P. Huijse, P. Protopapas, I. Reyes, J. Martínez-Palomera, C. Donoso. "Deep learning for image sequence classification of astronomical events." Publications of the Astronomical Society of the Pacific 131(1004), 108006 (2019).</li>
-                        
-                        <li>M. Mattheakis, P. Protopapas, D. Sondak, M. Di Giovanni, E. Kaxiras. "Physical symmetries embedded in neural networks." arXiv preprint arXiv:1904.08991 (2019).</li>
-                        
-                        <li>M. Pérez-Carrasco, G. Cabrera-Vives, M. Martinez-Marin, P. Cerulo, R. Demarco, P. Protopapas, J. Godoy. "Multiband galaxy morphologies for CLASH: a convolutional neural network transferred from CANDELS." Publications of the Astronomical Society of the Pacific 131(1004), 108002 (2019).</li>
-                        
-                        <li>C. Pieringer, K. Pichara, M. Catelán, P. Protopapas. "An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves." Monthly Notices of the Royal Astronomical Society 484(3), 3071-3077 (2019).</li>
-                        
-                        <li>J. Astudillo, P. Protopapas, K. Pichara, P. Huijse. "An Information Theory Approach on Deciding Spectroscopic Follow-ups." The Astronomical Journal 159(1), 16 (2019).</li>
-                        
-                        <li>A. Bianchi, M.R. Vendra, P. Protopapas, M. Brambilla. "Improving image classification robustness through selective CNN-filters fine-tuning." arXiv preprint arXiv:1904.03949 (2019).</li>
-                        
-                        <li>B. Saldias-Fuentes, P. Protopapas. "A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification." Proceedings of the 2019 SIAM International Conference on Data Mining, 756-764 (2019).</li>
-                        
-                        <li>M.J. Holman, M.J. Payne, W. Fraser, P. Lacerda, M.T. Bannister, M. Lackner, Y.T. Chen, H.W. Lin, K.W. Smith, R. Kokotanekova, D. Young. "A dwarf planet class object in the 21:5 resonance with Neptune." The Astrophysical Journal Letters 855(1), L6 (2018).</li>
-                        
-                        <li>G. Ramponi, P. Protopapas, M. Brambilla, R. Janssen. "T-cgan: Conditional generative adversarial network for data augmentation in noisy time series with irregular sampling." arXiv preprint arXiv:1811.08295 (2018).</li>
-                        
-                        <li>J. Martínez-Palomera, F. Förster, P. Protopapas, J.C. Maureira, P. Lira, G. Cabrera-Vives, P. Huijse, L. Galbany, T. De Jaeger, S. González-Gaitán, G. Medina. "The High Cadence Transit Survey (HiTS): Compilation and Characterization of Light-curve Catalogs." The Astronomical Journal 156(5), 186 (2018).</li>
-                        
-                        <li>P. Huijse, P.A. Estévez, F. Förster, S.F. Daniel, A.J. Connolly, P. Protopapas, R. Carrasco, J.C. Príncipe. "Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era." The Astrophysical Journal Supplement Series 236(1), 12 (2018).</li>
-                        
-                        <li>M. Belhaj, P. Protopapas, W. Pan. "Deep variational transfer: Transfer learning through semi-supervised deep generative models." arXiv preprint arXiv:1812.03123 (2018).</li>
-                        
-                        <li>J.R. Maat, N. Gianniotis, P. Protopapas. "Efficient optimization of echo state networks for time series datasets." 2018 International Joint Conference on Neural Networks (IJCNN), 1-7 (2018).</li>
-                        
-                        <li>N. Hoernle, K. Gal, B. Grosz, P. Protopapas, A. Rubin. "Modeling the Effects of Students' Interactions with Immersive Simulations Using Markov Switching Systems." International Educational Data Mining Society (2018).</li>
-                        
-                        <li>J.R. Martínez-Galarza, P. Protopapas, H.A. Smith, E.F. Morales. "Unraveling the Spectral Energy Distributions of Clustered YSOs." The Astrophysical Journal 864(1), 71 (2018).</li>
-                        
-                        <li>R.C. Davis, G. Cabrera-Vives, F. Förster, P.A. Estévez, P. Huijse, P. Protopapas, I. Reyes, J. Martínez, C. Donoso. "Deep Learning for Image Sequence Classification of Astronomical Events." arXiv preprint arXiv:1807.03869 (2018).</li>
-                        
-                        <li>Y.F. Jiang, P.J. Green, J.E. Greene, E. Morganson, Y. Shen, A. Pancoast, C.L. MacLeod, S.F. Anderson, W.N. Brandt, C.J. Grier, H.W. Rix. "Detection of time lags between quasar continuum emission bands based on Pan-STARRS light curves." The Astrophysical Journal 836(2), 186 (2017).</li>
-                        
-                        <li>P. Benavente, P. Protopapas, K. Pichara. "Automatic survey-invariant classification of variable stars." The Astrophysical Journal 845(2), 147 (2017).</li>
-
-                        <li>Yago Bea, Raúl Jiménez, David Mateos, Shuheng Liu, Pavlos Protopapas, Pedro Tarancón-Álvarez, Pablo Tejerina-Pérez. "Gravitational Duals from Equations of State." arXiv preprint arXiv:2403.14763 (2024).</li>
-  
-                        <li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin. "IoT Malware Data Augmentation using a Generative Adversarial Network." HICSS 2024: 7572-7581.</li>
-                        
-                        <li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin. "Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings." HICSS 2024: 7582-7591.</li>
-                        
-                        <li>Marios Mattheakis, Hayden Joy, Pavlos Protopapas. "A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function." CoRR abs/2101.06100 (2021) (Note: This appears to be a journal publication in 2023 of a 2021 preprint).</li>
-                        
-                        <li>R Pellegrin, B Bullwinkel, M Mattheakis, P Protopapas. "Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows" (2023)</li>
-                        
-                        <li>O Graf, P Flores, P Protopapas, K Pichara. "Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks" (2023)</li>
-                        
-                        <li>Blake Bullwinkel, Dylan Randle, Pavlos Protopapas, David Sondak. "Deqgan: Learning the loss function for pinns with generative adversarial networks" (2023)</li>
-                        
-                        <li>S Liu, X Huang, P Protopapas. "Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems" (2023)</li>
-                        
-                        <li>Hayden Joy, Marios Mattheakis, Pavlos Protopapas. "RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization" (2023)</li>
-                        
-                        <li>F Förster, G Cabrera-Vives, E Castillo-Navarrete, PA Estévez, ... P Protopapas, et al. "The automatic learning for the rapid classification of events (ALeRCE) alert broker" (2021)</li>
-                        
-                        <li>M Mattheakis, D Sondak, AS Dogra, P Protopapas. "Hamiltonian neural networks for solving equations of motion" (2022)</li>
-
-                        <li>Pellegrin, R., Bullwinkel, B., Mattheakis, M., Protopapas, P., "Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows" (2023)</li>
-  
-                        <li>Graf, O., Flores, P., Protopapas, P., Pichara, K., "Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks" (2023)</li>
-                        
-                        <li>Bullwinkel, B., Randle, D., Protopapas, P., Sondak, D., "Deqgan: Learning the loss function for pinns with generative adversarial networks" (2023)</li>
-                        
-                        <li>Liu, S., Huang, X., Protopapas, P., "Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems" (2023)</li>
-                        
-                        <li>Joy, H., Mattheakis, M., Protopapas, P., "RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization" (2023)</li>
-                        
-                        <li>Förster, F., Cabrera-Vives, G., Castillo-Navarrete, E., Estévez, P.A., ... Protopapas, P., et al., "The automatic learning for the rapid classification of events (ALeRCE) alert broker" (2021)</li>
-                        
-                        <li>Mattheakis, M., Sondak, D., Dogra, A.S., Protopapas, P., "Hamiltonian neural networks for solving equations of motion" (2022)</li>
-                        <li>
-                            Ferreira, T. A. E., Mattheakis, M., and Protopapas, P., <em>A New Artificial 
-              Neuron Proposal with Trainable Simultaneous Local and Global Activation Function</em>, 2021, <i>arXiv:2101.06100</i> [<a href="Pub/Tiago2021.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            D, Sondak, P. Protopapas, <em>Learning a Reduced Basis of Dynamical Systems using an Autoencoder
-        </em>, 2020, arXiv:2011.07346 [<a href="Pub/Sondak2020.pdf" target="_blank">pdf</a>]
-                        </li>
-                        <li>
-                            Fang, R., Sondak, D., Protopapas, P. and Succi, S.,
-                            <em>Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow. </em>, 2020, Journal of Turbulence, 21(9-10), pp.525-543 [<a href="Pub/Rui2020.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Zorich, L., Pichara, K. and Protopapas, P.,
-                            <em>Streaming classification of variable stars. Monthly Notices of the Royal Astronomical Society </em>, 2020, 492(2), pp.2897-2909 [<a href="Pub/Zorich2020.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Flamant, C., Protopapas, P. and Sondak, D.,
-                            <em>Solving Differential Equations Using Neural Network Solution Bundles</em>, 2020, arXiv preprint arXiv:2006.14372, [
-                            <a href="Pub/Cedric2020.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Chen, F., Sondak, D., Protopapas, P., Mattheakis, M., Liu, S., Agarwal, D. and Di Giovanni, M.,
-                            <em> NeuroDiffEq: A Python package for solving differential equations with neural networks </em>, 2020, Journal of Open Source Software, 5(46), p.1931 [<a href="Pub/Chen2020.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Astorga, N., Huijse, P., Protopapas, P. and Estévez, P.,
-                            <em>Matching Priors and Conditionals for Clustering</em>, 2020, August, MPCC, In European Conference on Computer Vision (pp. 658-677). Springer, Cham [<a href="Pub/Nicolas2020.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Wu, W., Protopapas, P., Yang, Z. and Michalatos, P.,
-                            <em> Gender classification and bias mitigation in facial images </em>, 2020. In 12th ACM Conference on Web Science (pp. 106-114) [<a href="Pub/Kali2020.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            H. Jin, M. Mattheakis, P. Protopapas, <em> Unsupervised Neural Networks for Quantum Eigenvalue Problems</em>, 2020, arXiv:2010.05075 [
-                            <a href="Pub/Henry2020.pdf">pdf</a>]</li>
-                        <li>
-                            Mattheakis, M., Sondak, D., Dogra, A.S. and Protopapas, P.,
-                            <em>Hamiltonian Neural Networks for solving differential equations </em>, 2020., arXiv:2001.11107 [<a href="Pub/MariosArxiv2020.pdf">pdf</a>]
-                        </li>
-
-
-                        <li>
-                            Paticchio, A., Scarlatti, T., Mattheakis, M., Protopapas, P., and Brambilla, M.,
-                            <em>Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread</em>, <i>arXiv e-prints: 2020arXiv201005074P </i>, 2020, [<a href='Pub/Ale2020.pdf'>pdf</a> </li>
-                        </li>
-                        <li>
-                            Randle, D., Protopapas, P. and Sondak, D., <em>Unsupervised Learning of Solutions to Differential Equations with 
-            Generative Adversarial Networks</em>, 2020, arXiv preprint arXiv:2007.11133 [<a href="Pub/Dylan2020.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Carrasco-Davis, R., Cabrera-Vives, G., Förster, F., Estevez, P.A., Huijse, P., Protopapas, P., Reyes, I., Martínez-Palomera, J. and Donoso, C.,
-                            <em> Deep learning for image sequence classification of astronomical events </em>, 2019, Publications of the Astronomical Society of the Pacific, 131(1004), p.108006 [<a href="Pub/Carrasco2019.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Mattheakis, M., Protopapas, P., Sondak, D., Di Giovanni, M. and Kaxiras, E.,
-                            <em> Physical symmetries embedded in neural networks </em>, 2019, arXiv preprint arXiv:1904.08991 [<a href="Pub/Marios2019.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Pérez-Carrasco, M., Cabrera-Vives, G., Martinez-Marin, M., Cerulo, P., Demarco, R., Protopapas, P. and Godoy, J.,
-                            <em> Multiband galaxy morphologies for CLASH: a convolutional neural network transferred from CANDELS, </em>2019, Publications of the Astronomical Society of the Pacific, 131(1004), p.108002 [<a href="Pub/Manolo2019.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Pieringer, C., Pichara, K., Catelán, M. and Protopapas, P.,
-                            <em>An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves</em>, 2019, Monthly Notices of the Royal Astronomical Society, 484(3), pp.3071-3077 [<a href="Pub/Cristian2019.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Astudillo, J., Protopapas, P., Pichara, K. and Huijse, P., <em>An Information Theory Approach on Deciding Spectroscopic Follow-ups</em>, 2019, The Astronomical Journal, 159(1), p.16 [<a href="Pub/Astudillo2019.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Bianchi, A., Vendra, M.R., Protopapas, P. and Brambilla, M.,
-                            <em>Improving image classification robustness through selective CNN-filters fine-tuning </em>, 2019, arXiv preprint arXiv:1904.03949. [
-                            <a href="Pub/Bianchi2019.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Saldias-Fuentes, B. and Protopapas, P.,
-                            <em>A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification </em>, 2019, In Proceedings of the 2019 SIAM International Conference on Data Mining (pp. 756-764). Society for Industrial and Applied
-                            Mathematics. [
-                            <a href="Pub/Belen2019.pdf">pdf</a>]
-                        </li>
-
-                        <li>
-                            Holman, M.J., Payne, M.J., Fraser, W., Lacerda, P., Bannister, M.T., Lackner, M., Chen, Y.T., Lin, H.W., Smith, K.W., Kokotanekova, R. and Young, D.,
-                            <em> A dwarf planet class object in the 21: 5 resonance with Neptune</em>, 2018, The Astrophysical Journal Letters, 855(1), p.L6 [
-                            <a href="Pub/Holman2018.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Ramponi, G., Protopapas, P., Brambilla, M. and Janssen, R.,
-                            <em> T-cgan: Conditional generative adversarial network for data augmentation in noisy time series with irregular sampling </em>, 2018, arXiv preprint arXiv:1811.08295 [
-                            <a href="Pub/Georgia2018.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Martínez-Palomera, J., Förster, F., Protopapas, P., Maureira, J.C., Lira, P., Cabrera-Vives, G., Huijse, P., Galbany, L., De Jaeger, T., González-Gaitán, S. and Medina, G.,
-                            <em> The High Cadence Transit Survey (HiTS): Compilation and Characterization of Light-curve Catalogs </em>, 2018, The Astronomical Journal, 156(5), p.186. [
-                            <a href="Pub/Jorge2018.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Huijse, P., Estévez, P.A., Förster, F., Daniel, S.F., Connolly, A.J., Protopapas, P., Carrasco, R. and Príncipe, J.C.,
-                            <em> Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era.
-             The Astrophysical Journal Supplement Series</em>, 2018, 236(1), p.12 [
-                            <a href="Pub/Pablo2018.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Belhaj, M., Protopapas, P. and Pan, W.,
-                            <em>Deep variational transfer: Transfer learning through semi-supervised deep generative models</em>, 2018, arXiv preprint arXiv:1812.03123 [
-                            <a href="Pub/Marouan2018.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Maat, J.R., Gianniotis, N. and Protopapas, P.,
-                            <em> July. Efficient optimization of echo state networks for time series datasets</em>, 2018, In 2018 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE [
-                            <a href="Pub/Reinier2018.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Hoernle, N., Gal, K., Grosz, B., Protopapas, P. and Rubin, A.,
-                            <em> Modeling the Effects of Students' Interactions with Immersive Simulations Using Markov Switching Systems</em>, 2018, International Educational Data Mining Society [
-                            <a href="Pub/Nick2018.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Martínez-Galarza, J.R., Protopapas, P., Smith, H.A. and Morales, E.F.,
-                            <em>Unraveling the Spectral Energy Distributions of Clustered YSOs</em>, 2018, The Astrophysical Journal, 864(1), p.71. [
-                            <a href="Pub/Rafael2018.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Davis, R.C., Cabrera-Vives, G., Förster, F., Estévez, P.A., Huijse, P., Protopapas, P., Reyes, I., Martínez, J. and Donoso, C.,
-                            <em>Deep Learning for Image Sequence Classification of Astronomical Events</em>, 2018, arXiv preprint arXiv:1807.03869 [
-                            <a href="Pub/Rodrigo2018.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Jiang, Y.F., Green, P.J., Greene, J.E., Morganson, E., Shen, Y., Pancoast, A., MacLeod, C.L., Anderson, S.F., Brandt, W.N., Grier, C.J. and Rix, H.W., <em>Detection of time lags between quasar continuum emission bands based on Pan-STARRS light curves</em>,
-                            2017, The Astrophysical Journal, 836(2), p.186 [<a href="Pub/Holman2017.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Benavente, P., Protopapas, P. and Pichara, K.,
-                            <em>Automatic survey-invariant classification of variable stars</em>, 2017, The Astrophysical Journal, 845(2), p.147 [
-                            <a href="Pub/Patricio2017.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Castro, N., Protopapas, P. and Pichara, K.,
-                            <em>Uncertain classification of variable stars: handling observational GAPS and noise</em>, 2017, The Astronomical Journal, 155(1), p.16 [
-                            <a href="Pub/Nicolas2017.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Protopapas, P., <em>Recurrent Neural Network Applications for Astronomical Time Series</em>, 2017, In American Astronomical Society Meeting Abstracts# 230 (Vol. 230, pp. 104-03). [
-                            <a href="Pub/Protopapas2017.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Mackenzie, C., Pichara, K. and Protopapas, P.,
-                            <em>Clustering-based feature learning on variable stars</em>, 2016, The Astrophysical Journal, 820(2), p.138 [
-                            <a href="Pub/Cristobal2016.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Pichara, K., Protopapas, P. and León, D.,
-                            <em>Meta-classification for variable stars</em>, 2016, The Astrophysical Journal, 819(1), p.18 [
-                            <a href="Pub/Karim2016.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Narasimhan, H., Pan, W., Kar, P., Protopapas, P. and Ramaswamy, H.G.,
-                            <em>December. Optimizing the multiclass F-measure via biconcave programming</em>, 2016, In 2016 IEEE 16th international conference on data mining (ICDM) (pp. 1101-1106). IEEE [
-                            <a href="Pub/Hari2016.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Nun, I., Protopapas, P., Sim, B. and Chen, W.,
-                            <em>Ensemble learning method for outlier detection and its application to astronomical light curves</em> The Astronomical Journal, 152(3), p.71 [
-                            <a href="Pub/Isadora2016.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Kim, R., <em> Empirical Methods in Peer Prediction (Doctoral dissertation) </em> [
-                            <a href="Pub/Kim2016.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Xia, X., Protopapas, P. and Doshi-Velez, F.,
-                            <em>Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice</em> In Proceedings of the 2016 SIAM International Conference on Data Mining (pp. 477-485).
-                            Society for Industrial and Applied Mathematics [
-                            <a href="Pub/Xia2016.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Nun, I., Protopapas, P., Sim, B., Zhu, M., Dave, R., Castro, N. and Pichara, K., <em>Fats: Feature analysis for time series</em>, 2105, arXiv preprint arXiv:1506.00010 [
-                            <a href="Pub/Isadora2015.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Protopapas, P., Huijse, P., Estevez, P.A., Zegers, P., Principe, J.C. and Marquette, J.B.,
-                            <em>A novel, fully automated pipeline for period estimation in the eros 2 data set</em>, 2015, The Astrophysical Journal Supplement Series, 216(2), p.25 [
-                            <a href="Pub/Pavlos2015.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Yang, J.J., Wang, X., Protopapas, P. and Bornn, L.,
-                            <em>Fast and optimal nonparametric sequential design for astronomical observations</em>, 2015, arXiv preprint arXiv:1501.02467 [
-                            <a href="Pub/Yang2015.pdf">pdf</a>]
-                        </li>
-
-                        <li>
-                            Kim, D.W., Protopapas, P., Bailer-Jones, C.A., Byun, Y.I., Chang, S.W., Marquette, J.B. and Shin, M.S.,
-                            <em>The EPOCH Project-I. Periodic variable stars in the EROS-2 LMC database</em>, 21014, Astronomy & Astrophysics, 566, p.A43 [
-                            <a href="Pub/daewon2014.pdf">pdf</a>]
-                        </li>
-
-                        <li>
-                            Huijse, P., Estevez, P.A., Protopapas, P., Principe, J.C. and Zegers, P.,
-                            <em>Computational intelligence challenges and applications on large-scale astronomical time series databases</em>, 2014, IEEE Computational Intelligence Magazine, 9(3), pp.27-39 [
-                            <a href="Pub/Pablo2014.pdf">pdf</a>]
-                        </li>
-
-                        <li>
-                            Nun, I., Pichara, K., Protopapas, P. and Kim, D.W.,
-                            <em>Supervised detection of anomalous light curves in massive astronomical catalogs</em>, 2014 The Astrophysical Journal, 793(1), p.23 [
-                            <a href="Pub/Isadora2014.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Verde, L., Protopapas, P. and Jimenez, R.,
-                            <em>The expansion rate of the intermediate universe in light of Planck</em>, 2014, Physics of the Dark Universe, 5, pp.307-314 [
-                            <a href="Pub/Licia2014.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Verde, L., Protopapas, P. and Jimenez, R.,
-                            <em>Planck and the local Universe: Quantifying the tension</em>, 2013, Physics of the Dark Universe, 2(3), pp.166-175 [
-                            <a href="Pub/Licia2013.pdf">pdf</a>]
-
-                        </li>
-
-                        <li>
-                            Pichara, K. and Protopapas, P.,
-                            <em>Automatic classification of variable stars in catalogs with missing data</em>, 2103, The Astrophysical Journal, 777(2), p.83 [
-                            <a href="Pub/Karim2013.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Chang, S.W., Protopapas, P., Kim, D.W. and Byun, Y.I.,
-                            <em>Statistical properties of Galactic δ Scuti stars: revisited</em>, 2013, The Astronomical Journal, 145(5), p.132 [
-                            <a href="Pub/Daewon2013.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Huijse, P., Estevez, P.A., Protopapas, P., Zegers, P. and Principe, J.C.,
-                            <em>An information theoretic algorithm for finding periodicities in stellar light curves</em>, 2012, IEEE Transactions on Signal Processing, 60(10), pp.5135-5145 [
-                            <a href="Pub/Pablo2012.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Pichara, K., Protopapas, P., Kim, D.W., Marquette, J.B. and Tisserand, P.,
-                            <em>An improved quasar detection method in EROS-2 and MACHO LMC data sets</em>, 2012, Monthly Notices of the Royal Astronomical Society, 427(2), pp.1284-1297 [
-                            <a href="Pub/Karim2012.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Wang, Y., Khardon, R. and Protopapas, P.,
-                            <em>Nonparametric Bayesian estimation of periodic light curves</em> 2012, The Astrophysical Journal, 756(1), p.67 [
-                            <a href="Pub/Roni2012.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Kim, D.W., Protopapas, P., Trichas, M., Rowan-Robinson, M., Khardon, R., Alcock, C. and Byun, Y.I.,
-                            <em>A Refined QSO Selection Method Using Diagnostics Tests: 663 QSO Candidates in the Large Magellanic Cloud</em> The Astrophysical Journal, 747(2), p.107 [
-                            <a href="Pub/Daewon2012.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Blocker, A.W. and Protopapas, P.,
-                            <em>Semi-parametric robust event detection for massive time-domain databases</em>, 2012, In Statistical Challenges in Modern Astronomy V (pp. 177-187). Springer, New York, NY [
-                            <a href="Pub/Alex2012.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Wang, Y., Khardon, R. and Protopapas, P.,
-                            <em>Infinite shift-invariant grouped multi-task learning for gaussian processes</em>, 2012, arXiv preprint arXiv:1203.0970 [
-                            <a href="Pub/wang2012.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Huijse, P., Estévez, P.A., Protopapas, P., Zegers, P. and Príncipe, J.C.,
-                            <em>Computational Challenges in Processing Very Large Astronomical Survey Databases</em>, 2012, In 2012 9th Asia-Pacific Symposium on Information and Telecommunication Technologies (APSITT) (pp. 1-6). IEEE [
-                            <a href="Pub/Pablo2012.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Kim, D.W., Protopapas, P., Byun, Y.I., Alcock, C., Khardon, R. and Trichas, M.,
-                            <em>Quasi-stellar object selection algorithm using time variability and machine learning: Selection of 1620 quasi-stellar object candidates from MACHO Large Magellanic Cloud database</em> ,2011, The Astrophysical Journal, 735(2),
-                            p.68 [
-                            <a href="Pub/Daewon2011.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Huijse, P., Estévez, P.A., Zegers, P., Príncipe, J.C. and Protopapas, P.,
-                            <em>Period estimation in astronomical time series using slotted correntropy</em>, 2011, IEEE Signal Processing Letters, 18(6), pp.371-374 [
-                            <a href="Pub/Pablos2011.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Wang, Y., Khardon, R. and Protopapas, P.,
-                            <em> Nonparametric Bayesian estimation of periodic functions</em> 2011, arXiv preprint arXiv:1111.1315 [
-                            <a href="Pub/Wang2011.pdf">pdf</a>]
-
-                        </li>
-                        <li>
-                            Mishra, B.P., Principe, J.C., Estevez, P.A. and Protopapas, P.,
-                            <em></Estimation of periodicity in non-uniformly sampled astronomical data using a 2D kernel in correntropy</em> 2011, In 2011 IEEE International Workshop on Machine Learning for Signal Processing (pp. 1-6). IEEE [
-                            <a href="Pub/Mishra2011.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Fuentes, C.I., Holman, M.J., Trilling, D.E. and Protopapas, P.,
-                            <em>Trans-Neptunian objects with Hubble Space Telescope ACS/WFC</em> 2011, The Astrophysical Journal, 722(2), p.1290 [
-                            <a href="Pub/Cesar2010.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Wang, Y., Khardon, R. and Protopapas, P.,
-                            <em>Shift-invariant grouped multi-task learning for Gaussian processes</em>, 2010, In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 418-434). Springer, Berlin, Heidelberg [
-                            <a href="Pub/Wang2010.pdf">pdf</a>]
-                        </li>
-                        <li>
-                            Estévez, P.A., Huijse, P., Zegers, P., Principe, J.C. and Protopapas, P.,
-                            <em>Period detection in light curves from astronomical objects using correntropy</em>, 2010, In The 2010 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE [
-                            <a href="Pub/Pablos2010.pdf">pdf</a>]
-                        </li>
-
-
-
-
-                        <li>
-                            U. Rebbapragada, P. Protopapas, C. Brodley, C. Alcock, <em>Finding Anomalies in Periodic Time Series</em>, Machine Learning, p. 281, vol. 74, (<span class="style5">2009</span>) [<a href="Pub/Umaa2009.pdf">pdf</a>]</li>
-                        <li>
-                            S. Pember, C. Brodley, P. Protopapas, and A. Kilmer, <em>Similarity Retrieval in Large Datasets using Rank Revealing QR</em>, ICDM, &nbsp;Under review at IEEE PAMI, (<span class="style5">2009</span>).<br />
-                        </li>
-                        <li>
-                            Dan Preston, Pavlos Protopapas and Carla Brodley<em>, Event Detection in Time Series</em>, Proceedings of the Ninth SIAM International Conference on Data Mining, p. 61-72, (<span class="style5">2009</span>) [<a href="Pub/prestondSIAM.pdf"
-                                target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            Dan Preston, Pavlos Protopapas and Carla Brodley, <em>Discovering Arbitrary Event Types in Time Series,</em> SIAM Best of 09 SDM, (<span class="style5">2009</span>)<br /></li>
-                        <li>
-                            Dae-Won Kim, Pavlos Protopapas, Charles Alcock, Yong-Ik Byun, Federica Bianco<em>, Detection of Flare Stars in TAOS 2-year Data</em>, The Astronomer's Telegram, vol. #2035, (<span class="style5">2009</span>) [<a href="http://www.astronomerstelegram.org/?read=2035"
-                                target="_blank">html</a>] <br />
-                        </li>
-                        <li>
-                            Gabriel Wachman, Roni Khardon, Pavlos Protopapas, Charles R. Alcock, <em>Kernels for Periodic Time Series Arising in Astronomy</em>, ECML PKDD, (<span class="style5">2009</span>) [<a href="Pub/Wachman2009.pdf" target="_blank">pdf</a>]<br
-                            />
-                        </li>
-                        <li>
-                            Dae-Won Kim, Pavlos Protopapas, Yong-Ik Byun, Charles Alcock and the TAOS collaboration, <em>The TAOS Project Stellar Variability I. Detection of Low-Amplitude δ Scuti Stars and a Revised Catalog of All Known δ Scuti Stars,</em>                            submitted to Astronomical Journal, (<span class="style5">2009</span>) [<a href="Pub/DSC2009.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            J.~H. Wang, P.&nbsp; Protopapas, W. –P. Chen, C. R. Alcock, &nbsp;W. S. Burgett, T. Dombeck, J. S. Morgan, P. A. Price, J. L. Tonry, <em>Searching for sub-kilometer TNOs using Pan-STARRS video mode lightcurves:</em><strong> </strong><em>Preliminary study and evaluation using engineering data, </em>submitted
-                            to Astronomical Journal, &nbsp;(<span class="style5">2009</span>) [<a href="Pub/Wang2009.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            A. W. Blocker, P. Protopapas, C. R. Alcock<em>, A Bayesian approach to the analysis of time symmetry in light curves: Reconsidering Scorpius X-1 occultations</em>, The Astronomical Journal, Volume 138, Issue 2, pp. 568-578,
-                            (
-                            <span class="style5">2009</span>) [<a href="Pub/Blocker2009.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            F. Bianco, P. Protopapas, B. McLeod, C. R. Alcock,&nbsp; M. J.&nbsp; Holman, M. J. Lehner. <em>A Search for Occultations of Bright Stars by Small Kuiper Belt Objects using Megacam on the MMT, </em>The Astronomical Journal,
-                            Volume 138, Issue 2, pp. 568-578, (<span class="style5">2009</span>) [<a href="Pub/Bianco2009.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            D-W Kim, P. Protopapas, C. Alcock, B. Yong-Ik, F. Bianco,&nbsp; <em>De-Trending Time Series for Astronomical Variability Surveys</em>, Monthly Notices of the Royal Astronomical Society, Volume 397, Issue 2, pp. 558-568,<em> (2008)</em>                            [<a href="Pub/DaeWon-Detrend.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            R. E. Schild, &nbsp;J. Lovegrove, P. Protopapas, <em>Reverberation in the UV-Optical Continuum Brightness Fluctuations of MACHO Quasar</em>, The Astronomical Journal, Volume 138, Issue 2, pp. 421-427, (<span class="style5">2009</span>)
-                            [
-                            <a href="Pub/Schild2009.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            Zhan et al.<strong>, </strong><em>First Results from the Taiwanese-American Occultation Survey (TAOS)</em>, ApJL, 685, L157, (<span class="style5">2008</span>) [<a href="http://arxiv.org/pdf/0808.2051v1">pdf</a>]<br />
-                        </li>
-                        <li>
-                            E. Morikawa, R. Dave,&nbsp; P. Protopapas, <em>A Novel GUI Based Interactive Work Flow Application for Exploratory and Batch Processing of Light Curves, </em>Astronomical Data Analysis Software and Systems XVII, 394, 357, (
-                            <span class="style5">2008)</span> [<a href="Pub/Morikawa2007.pdf">pdf</a>]<br />
-                        </li>
-                        <li>
-                            Lorenzo Faccioli, Charles Alcock, Kem Cook, Gabriel E. Prochter, Pavlos Protopapas, David Syphers, <em>Eclipsing Binary Stars in the Large and Small Magellanic Clouds from the MACHO Project: The Sample</em>, AJ, 134, 1963-1994,
-                            <span class="style5">(2007) </span>[<a href="Pub/Faccioli2007.pdf">pdf</a>] <br />
-                        </li>
-                        <li>
-                            Holman, Matthew J.; Protopapas, P.; Tholen, D. J., <em>Searching for Solar System Wide Binaries with Pan-STARRS-1</em>, AAS, 39, 52, <span class="style5">(2007)</span><br /></li>
-                        <li>
-                            Dave, R.; Protopapas, P.; Lehner, M., <em>Virtual Astronomical Pipelines</em>, Astronomical Data Analysis Software and Systems XVI ASP Conference Series, Vol. 376, proceedings of the conference held 15-18 October in Tucson,
-                            Arizona, USA. Edited by Richard A. Shaw, Frank Hill and David J. Bell., p.253, <span class="style5">(2006)</span> [<a href="Pub/Dave2007.pdf">pdf</a>]<br />
-                        </li>
-                        <li>
-                            J. M. Diego, M. Tegmark, P. Protopapas, H. B. Sadvik, <em>Combined reconstruction of weak and strong lensing data with WSLAP</em>, MNRAS, 375, 958-970, <span class="style5">(2007)</span> [<a href="Pub/Diego2007.pdf">pdf</a>]<br
-                            />
-                        </li>
-                        <li>
-                            Eamonn Keogh, Li Wei, Xiaopeng Xi, Michail Vlachos, Sang-Hee Lee, Pavlos Protopapas. Supporting,<em> Exact Indexing of Shapes under Rotation Invariance with Arbitrary&nbsp; 
-            Representations and Distance Measures, </em>VLDB: 882-893, (<span class="style5">2006)</span> [<a href="Pub/Eamonn2008.pdf" target="_blank">pdf</a>] <br /></li>
-                        <li>
-                            P. Protopapas, J. M. Giammarco, L.&nbsp; Faccioli, M. F. Struble, R. Dave , C. Alcock, <em>Finding outlier light-curves in catalogs of periodic variable stars</em>, MNRAS, 369, 677,
-                            <span class="style5">(<em>2006)</em> </span>[<a href="Pub/Giammarco2006.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            Pavlos Protopapas, Raul Jimenez , Charles Alcock , <em>Fast identification of transits from light-curves</em>, MNRAS, 362, 460, <span class="style5">(2005)</span> [
-                            <a href="Pub/Jimenez2005.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            J. M. Diego, H. B. Sadvik, P. Protopapas, M. Tegmark, N. Benitez, T. Broadhurst, <em>Non-parametric mass reconstruction of A1689 from strong lensing data with SLAP</em>, MNRAS, 362, 1247,
-                            <span class="style5">(2005)</span> [<a href="Pub/Diego2005b.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            J. M. Diego, P. Protopapas, H. B. Sadvik, M. Tegmark, <em>Non-parametric inversion of strong lensing systems</em>, MNRAS, 360, 477, (<span class="style5">2005)</span> [<a href="Pub/Diego2005.pdf" target="_blank">pdf</a>]<br
-                            />
-                        </li>
-                        <li>
-                            A. Klein, P. Protopapas, S. G. Rohoziński, K. Starosta, <em>Kerman-Klein-Dönau-Frauendorf model for odd-odd nuclei: Formal theory</em>,&nbsp; Physical Review C,&nbsp; vol. 69, Issue 3, id. 034338,
-                            <span class="style5"> (2005)</span> [<a href="Pub/PhysRevC.69.034338.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            R. D. Amado, M. Á. Halász, P. Protopapas, <em>Two Skyrmion dynamics with ω mesons</em><strong>,</strong> Physical Review D (Particles and Fields), Volume 61, Issue 7, (<span class="style5">2000)</span> [<a href="Pub/PhysRevD.61.074022.pdf"
-                                target="_blank">pdf</a>] <br /></li>
-                        <li>
-                            Y. Lu, P. Protopapas, R. D. Amado, <em>Nucleon-antinucleon interaction from the Skyrme model. II. Beyond the product ansatz</em>, Physical Review C, 57, 1983-1990, (<span class="style5">1998)</span> [<a href="Pub/PhysRevC.57.1983.pdf"
-                                target="_blank">pdf</a>] <br /></li>
-                        <li>
-                            P. Protopapas, A. Klein, <em>Possible solution of the Coriolis attenuation problem</em>, <span class="style5">(1997)</span>, Phys. Rev. C,&nbsp; 55, 1810-1818 [
-                            <a href="Pub/PhysRevC.55.1810.pdf" target="_blank">pdf</a>] <br />
-                        </li>
-                        <li>
-                            P. Protopapas, A. Klein, <em>Derivation and assessment of strong coupling core-particle model from the Kerman-Klein-Dönau-Frauendorf theory</em>,
-                            <span class="style5">(1997)</span><strong>, </strong>Physical Review C (Nuclear Physics), Volume 55, Issue 2, pp.699-713 [<a href="Pub/PhysRevC.55.699.pdf" target="_blank">pdf</a>] <br />
-                        </li>
-                        <li>
-                            P. Protopapas, A. Klein, <em>Application of the Kerman-Klein Method to the Solution of a Spherical Shell Model for a Deformed Rare-Earth Nucleus</em>,
-                            <span class="style5">(1997)</span>,&nbsp; Physical Review Letters, Volume 78, Issue 23, June 9, pp.4347-4350 [<a href="Pub/PhysRevLett.78.4347.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            P. Protopapas, A. Klein, N. R. Walet,<em> Further application of a semimicroscopic core-particle coupling method to the properties of 155,157Gd and 159Dy</em>,
-                            <span class="style5">(1996)</span>, Physical Review C (Nuclear Physics), Volume 53, Issue 4, April pp.1655-1659 [<a href="Pub/PhysRevC.53.1655.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            P. Protopapas, A. Klein, N. R. Walet,<em> Application of a semimicroscopic core-particle coupling method to the backbending in odd deformed nuclei</em>, <span class="style5">(1996)
-            <strong></strong></span><strong>, </strong>Physical Review C (Nuclear Physics), Volume 54, Issue 2, pp.638-645 [<a href="Pub/PhysRevC.54.638.pdf" target="_blank">pdf</a>]<br />
-                        </li>
-                        <li>
-                            P. Protopapas, A. Klein, N. R. Walet,<em> Calculation of the properties of the rotational bands of 155,157Gd</em>, <span class="style5">(1994), 
-            </span>Physical Review C (Nuclear Physics), Volume 50, Issue 1, pp.245-256 [<a href="Pub/PhysRevC.50.245.pdf" target="_blank">pdf</a>] </p>
-                            </p>
-                        </li>
+​                            "Positional Encodings for Light Curve Transformers: Playing with Positions and Attention." 
+​                            arXiv preprint arXiv:2308.06404 (2023).</li>
+                        <li>K. Ly, J. Kurlander, M. Holman, M. Payne, A. Heinze, P. Bernardinelli, et al. "2010 RJ226." Minor Planet Electronic Circulars 2023.</li><li>J. Carter, S. Mancoridis, P. Protopapas. "Optimal data sample length for system call traces for malware detection in an iot ecosystem." 2023 3rd International Conference on Electrical, Computer, Communications and Electronics Engineering.</li><li>S. Liu, X. Huang, P. Protopapas. "Residual-based error bound for physics-informed neural networks." Uncertainty in Artificial Intelligence, 1284-1293 (2023).</li><li>A.T. Chantada, S.J. Landau, P. Protopapas, C.G. Scóccola, C. Garraffo. "Cosmology-informed neural networks to solve the background dynamics of the Universe." Physical Review D 107 (6), 063523 (2023).</li><li>M. Mattheakis, H. Joy, P. Protopapas. "Reservoir Computing for Solving Ordinary Differential Equations." International Journal on Artificial Intelligence Tools 32 (01), 2350030 (2023).</li><li>J. Astudillo, P. Protopapas, K. Pichara, I. Becker. "A Reinforcement Learning–Based Follow-up Framework." The Astronomical Journal 165 (3), 118 (2023).</li><li>C. Donoso-Oliva, I. Becker, P. Protopapas, G. Cabrera-Vives, M. Vishnu, et al. "ASTROMER-A transformer-based embedding for the representation of light curves." Astronomy &amp; Astrophysics 670, A54 (2023).</li><li>T. Allen, F. Grezes, G. Shapurian, S. Blanco-Cuaresma, C. Grant, et al. "ADS Machine Learning and Deep Learning Efforts." American Astronomical Society Meeting Abstracts 55 (2), 177.37 (2023).</li><li>T.A.E. Ferreira, M. Mattheakis, P. Protopapas. "A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function." arXiv:2101.06100 (2021).</li><li>D. Sondak, P. Protopapas. "Learning a Reduced Basis of Dynamical Systems using an Autoencoder." arXiv:2011.07346 (2020).</li><li>R. Fang, D. Sondak, P. Protopapas, S. Succi. "Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow." Journal of Turbulence 21(9-10), 525-543 (2020).</li><li>L. Zorich, K. Pichara, P. Protopapas. "Streaming classification of variable stars." Monthly Notices of the Royal Astronomical Society 492(2), 2897-2909 (2020).</li><li>C. Flamant, P. Protopapas, D. Sondak. "Solving Differential Equations Using Neural Network Solution Bundles." arXiv preprint arXiv:2006.14372 (2020).</li><li>F. Chen, D. Sondak, P. Protopapas, M. Mattheakis, S. Liu, D. Agarwal, M. Di Giovanni. "NeuroDiffEq: A Python package for solving differential equations with neural networks." Journal of Open Source Software 5(46), 1931 (2020).</li><li>N. Astorga, P. Huijse, P. Protopapas, P. Estévez. "Matching Priors and Conditionals for Clustering." European Conference on Computer Vision, 658-677 (2020).</li><li>W. Wu, P. Protopapas, Z. Yang, P. Michalatos. "Gender classification and bias mitigation in facial images." 12th ACM Conference on Web Science, 106-114 (2020).</li><li>H. Jin, M. Mattheakis, P. Protopapas. "Unsupervised Neural Networks for Quantum Eigenvalue Problems." arXiv:2010.05075 (2020).</li><li>M. Mattheakis, D. Sondak, A.S. Dogra, P. Protopapas. "Hamiltonian Neural Networks for solving differential equations." arXiv:2001.11107 (2020).</li><li>A. Paticchio, T. Scarlatti, M. Mattheakis, P. Protopapas, M. Brambilla. "Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread." arXiv e-prints: 2020arXiv201005074P (2020).</li><li>D. Randle, P. Protopapas, D. Sondak. "Unsupervised Learning of Solutions to Differential Equations with Generative Adversarial Networks." arXiv preprint arXiv:2007.11133 (2020).</li><li>R. Carrasco-Davis, G. Cabrera-Vives, F. Förster, P.A. Estevez, P. Huijse, P. Protopapas, I. Reyes, J. Martínez-Palomera, C. Donoso. "Deep learning for image sequence classification of astronomical events." Publications of the Astronomical Society of the Pacific 131(1004), 108006 (2019).</li><li>M. Mattheakis, P. Protopapas, D. Sondak, M. Di Giovanni, E. Kaxiras. "Physical symmetries embedded in neural networks." arXiv preprint arXiv:1904.08991 (2019).</li><li>M. Pérez-Carrasco, G. Cabrera-Vives, M. Martinez-Marin, P. Cerulo, R. Demarco, P. Protopapas, J. Godoy. "Multiband galaxy morphologies for CLASH: a convolutional neural network transferred from CANDELS." Publications of the Astronomical Society of the Pacific 131(1004), 108002 (2019).</li><li>C. Pieringer, K. Pichara, M. Catelán, P. Protopapas. "An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves." Monthly Notices of the Royal Astronomical Society 484(3), 3071-3077 (2019).</li><li>J. Astudillo, P. Protopapas, K. Pichara, P. Huijse. "An Information Theory Approach on Deciding Spectroscopic Follow-ups." The Astronomical Journal 159(1), 16 (2019).</li><li>A. Bianchi, M.R. Vendra, P. Protopapas, M. Brambilla. "Improving image classification robustness through selective CNN-filters fine-tuning." arXiv preprint arXiv:1904.03949 (2019).</li><li>B. Saldias-Fuentes, P. Protopapas. "A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification." Proceedings of the 2019 SIAM International Conference on Data Mining, 756-764 (2019).</li><li>M.J. Holman, M.J. Payne, W. Fraser, P. Lacerda, M.T. Bannister, M. Lackner, Y.T. Chen, H.W. Lin, K.W. Smith, R. Kokotanekova, D. Young. "A dwarf planet class object in the 21:5 resonance with Neptune." The Astrophysical Journal Letters 855(1), L6 (2018).</li><li>G. Ramponi, P. Protopapas, M. Brambilla, R. Janssen. "T-cgan: Conditional generative adversarial network for data augmentation in noisy time series with irregular sampling." arXiv preprint arXiv:1811.08295 (2018).</li><li>J. Martínez-Palomera, F. Förster, P. Protopapas, J.C. Maureira, P. Lira, G. Cabrera-Vives, P. Huijse, L. Galbany, T. De Jaeger, S. González-Gaitán, G. Medina. "The High Cadence Transit Survey (HiTS): Compilation and Characterization of Light-curve Catalogs." The Astronomical Journal 156(5), 186 (2018).</li><li>P. Huijse, P.A. Estévez, F. Förster, S.F. Daniel, A.J. Connolly, P. Protopapas, R. Carrasco, J.C. Príncipe. "Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era." The Astrophysical Journal Supplement Series 236(1), 12 (2018).</li><li>M. Belhaj, P. Protopapas, W. Pan. "Deep variational transfer: Transfer learning through semi-supervised deep generative models." arXiv preprint arXiv:1812.03123 (2018).</li><li>J.R. Maat, N. Gianniotis, P. Protopapas. "Efficient optimization of echo state networks for time series datasets." 2018 International Joint Conference on Neural Networks (IJCNN), 1-7 (2018).</li><li>N. Hoernle, K. Gal, B. Grosz, P. Protopapas, A. Rubin. "Modeling the Effects of Students' Interactions with Immersive Simulations Using Markov Switching Systems." International Educational Data Mining Society (2018).</li><li>J.R. Martínez-Galarza, P. Protopapas, H.A. Smith, E.F. Morales. "Unraveling the Spectral Energy Distributions of Clustered YSOs." The Astrophysical Journal 864(1), 71 (2018).</li><li>R.C. Davis, G. Cabrera-Vives, F. Förster, P.A. Estévez, P. Huijse, P. Protopapas, I. Reyes, J. Martínez, C. Donoso. "Deep Learning for Image Sequence Classification of Astronomical Events." arXiv preprint arXiv:1807.03869 (2018).</li><li>Y.F. Jiang, P.J. Green, J.E. Greene, E. Morganson, Y. Shen, A. Pancoast, C.L. MacLeod, S.F. Anderson, W.N. Brandt, C.J. Grier, H.W. Rix. "Detection of time lags between quasar continuum emission bands based on Pan-STARRS light curves." The Astrophysical Journal 836(2), 186 (2017).</li><li>P. Benavente, P. Protopapas, K. Pichara. "Automatic survey-invariant classification of variable stars." The Astrophysical Journal 845(2), 147 (2017).</li><li>Yago Bea, Raúl Jiménez, David Mateos, Shuheng Liu, Pavlos Protopapas, Pedro Tarancón-Álvarez, Pablo Tejerina-Pérez. "Gravitational Duals from Equations of State." arXiv preprint arXiv:2403.14763 (2024).</li><li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin. "IoT Malware Data Augmentation using a Generative Adversarial Network." HICSS 2024: 7572-7581.</li><li>John Carter, Spiros Mancoridis, Pavlos Protopapas, Erick Galinkin. "Behavioral Malware Detection using a Language Model Classifier Trained on sys2vec Embeddings." HICSS 2024: 7582-7591.</li><li>Marios Mattheakis, Hayden Joy, Pavlos Protopapas. "A New Artificial Neuron Proposal with Trainable Simultaneous Local and Global Activation Function." CoRR abs/2101.06100 (2021) (Note: This appears to be a journal publication in 2023 of a 2021 preprint).</li><li>R Pellegrin, B Bullwinkel, M Mattheakis, P Protopapas. "Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows" (2023)</li><li>O Graf, P Flores, P Protopapas, K Pichara. "Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks" (2023)</li><li>Blake Bullwinkel, Dylan Randle, Pavlos Protopapas, David Sondak. "Deqgan: Learning the loss function for pinns with generative adversarial networks" (2023)</li><li>S Liu, X Huang, P Protopapas. "Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems" (2023)</li><li>Hayden Joy, Marios Mattheakis, Pavlos Protopapas. "RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization" (2023)</li><li>F Förster, G Cabrera-Vives, E Castillo-Navarrete, PA Estévez, ... P Protopapas, et al. "The automatic learning for the rapid classification of events (ALeRCE) alert broker" (2021)</li><li>M Mattheakis, D Sondak, AS Dogra, P Protopapas. "Hamiltonian neural networks for solving equations of motion" (2022)</li><li>Pellegrin, R., Bullwinkel, B., Mattheakis, M., Protopapas, P., "Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows" (2023)</li><li>Graf, O., Flores, P., Protopapas, P., Pichara, K., "Error-Aware B-PINNs: Improving Uncertainty Quantification in Bayesian Physics-Informed Neural Networks" (2023)</li><li>Bullwinkel, B., Randle, D., Protopapas, P., Sondak, D., "Deqgan: Learning the loss function for pinns with generative adversarial networks" (2023)</li><li>Liu, S., Huang, X., Protopapas, P., "Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems" (2023)</li><li>Joy, H., Mattheakis, M., Protopapas, P., "RcTorch: a PyTorch Reservoir Computing Package with Automated Hyper-Parameter Optimization" (2023)</li><li>Förster, F., Cabrera-Vives, G., Castillo-Navarrete, E., Estévez, P.A., ... Protopapas, P., et al., "The automatic learning for the rapid classification of events (ALeRCE) alert broker" (2021)</li><li>Mattheakis, M., Sondak, D., Dogra, A.S., Protopapas, P., "Hamiltonian neural networks for solving equations of motion" (2022)</li><li>
+​                            Ferreira, T. A. E., Mattheakis, M., and Protopapas, P., <em>A New Artificial 
+​              Neuron Proposal with Trainable Simultaneous Local and Global Activation Function</em>, 2021, <i>arXiv:2101.06100</i> [<a href="Pub/Tiago2021.pdf">pdf</a>]
+​                        </li>
+                        <li>
+​                            D, Sondak, P. Protopapas, <em>Learning a Reduced Basis of Dynamical Systems using an Autoencoder
+​        </em>, 2020, arXiv:2011.07346 [<a href="Pub/Sondak2020.pdf" target="_blank">pdf</a>]
+​                        </li>
+                        <li>
+​                            Fang, R., Sondak, D., Protopapas, P. and Succi, S.,
+​                            <em>Neural network models for the anisotropic Reynolds stress tensor in turbulent channel flow. </em>, 2020, Journal of Turbulence, 21(9-10), pp.525-543 [<a href="Pub/Rui2020.pdf">pdf</a>]
+​                        </li><li>
+​                            Zorich, L., Pichara, K. and Protopapas, P.,
+​                            <em>Streaming classification of variable stars. Monthly Notices of the Royal Astronomical Society </em>, 2020, 492(2), pp.2897-2909 [<a href="Pub/Zorich2020.pdf">pdf</a>]
+​                        </li><li>
+​                            Flamant, C., Protopapas, P. and Sondak, D.,
+​                            <em>Solving Differential Equations Using Neural Network Solution Bundles</em>, 2020, arXiv preprint arXiv:2006.14372, [
+​                            <a href="Pub/Cedric2020.pdf">pdf</a>]
+​                        </li><li>
+​                            Chen, F., Sondak, D., Protopapas, P., Mattheakis, M., Liu, S., Agarwal, D. and Di Giovanni, M.,
+​                            <em> NeuroDiffEq: A Python package for solving differential equations with neural networks </em>, 2020, Journal of Open Source Software, 5(46), p.1931 [<a href="Pub/Chen2020.pdf">pdf</a>]
+​                        </li><li>
+​                            Astorga, N., Huijse, P., Protopapas, P. and Estévez, P.,
+​                            <em>Matching Priors and Conditionals for Clustering</em>, 2020, August, MPCC, In European Conference on Computer Vision (pp. 658-677). Springer, Cham [<a href="Pub/Nicolas2020.pdf">pdf</a>]
+​                        </li><li>
+​                            Wu, W., Protopapas, P., Yang, Z. and Michalatos, P.,
+​                            <em> Gender classification and bias mitigation in facial images </em>, 2020. In 12th ACM Conference on Web Science (pp. 106-114) [<a href="Pub/Kali2020.pdf">pdf</a>]
+​                        </li><li>
+​                            H. Jin, M. Mattheakis, P. Protopapas, <em> Unsupervised Neural Networks for Quantum Eigenvalue Problems</em>, 2020, arXiv:2010.05075 [
+​                            <a href="Pub/Henry2020.pdf">pdf</a>]</li><li>
+​                            Mattheakis, M., Sondak, D., Dogra, A.S. and Protopapas, P.,
+​                            <em>Hamiltonian Neural Networks for solving differential equations </em>, 2020., arXiv:2001.11107 [<a href="Pub/MariosArxiv2020.pdf">pdf</a>]
+​                        </li><li>
+​                            Paticchio, A., Scarlatti, T., Mattheakis, M., Protopapas, P., and Brambilla, M.,
+​                            <em>Semi-supervised Neural Networks solve an inverse problem for modeling Covid-19 spread</em>, <i>arXiv e-prints: 2020arXiv201005074P </i>, 2020, [<a href="Pub/Ale2020.pdf">pdf</a> </li><li>
+​                            Randle, D., Protopapas, P. and Sondak, D., <em>Unsupervised Learning of Solutions to Differential Equations with 
+​            Generative Adversarial Networks</em>, 2020, arXiv preprint arXiv:2007.11133 [<a href="Pub/Dylan2020.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Carrasco-Davis, R., Cabrera-Vives, G., Förster, F., Estevez, P.A., Huijse, P., Protopapas, P., Reyes, I., Martínez-Palomera, J. and Donoso, C.,
+​                            <em> Deep learning for image sequence classification of astronomical events </em>, 2019, Publications of the Astronomical Society of the Pacific, 131(1004), p.108006 [<a href="Pub/Carrasco2019.pdf">pdf</a>]
+​                        </li><li>
+​                            Mattheakis, M., Protopapas, P., Sondak, D., Di Giovanni, M. and Kaxiras, E.,
+​                            <em> Physical symmetries embedded in neural networks </em>, 2019, arXiv preprint arXiv:1904.08991 [<a href="Pub/Marios2019.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Pérez-Carrasco, M., Cabrera-Vives, G., Martinez-Marin, M., Cerulo, P., Demarco, R., Protopapas, P. and Godoy, J.,
+​                            <em> Multiband galaxy morphologies for CLASH: a convolutional neural network transferred from CANDELS, </em>2019, Publications of the Astronomical Society of the Pacific, 131(1004), p.108002 [<a href="Pub/Manolo2019.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Pieringer, C., Pichara, K., Catelán, M. and Protopapas, P.,
+​                            <em>An Algorithm for the Visualization of Relevant Patterns in Astronomical Light Curves</em>, 2019, Monthly Notices of the Royal Astronomical Society, 484(3), pp.3071-3077 [<a href="Pub/Cristian2019.pdf">pdf</a>]
+​                        </li><li>
+​                            Astudillo, J., Protopapas, P., Pichara, K. and Huijse, P., <em>An Information Theory Approach on Deciding Spectroscopic Follow-ups</em>, 2019, The Astronomical Journal, 159(1), p.16 [<a href="Pub/Astudillo2019.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Bianchi, A., Vendra, M.R., Protopapas, P. and Brambilla, M.,
+​                            <em>Improving image classification robustness through selective CNN-filters fine-tuning </em>, 2019, arXiv preprint arXiv:1904.03949. [
+​                            <a href="Pub/Bianchi2019.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Saldias-Fuentes, B. and Protopapas, P.,
+​                            <em>A Full Probabilistic Model for Yes/No Type Crowdsourcing in Multi-Class Classification </em>, 2019, In Proceedings of the 2019 SIAM International Conference on Data Mining (pp. 756-764). Society for Industrial and Applied
+​                            Mathematics. [
+​                            <a href="Pub/Belen2019.pdf">pdf</a>]
+​                        </li><li>
+​                            Holman, M.J., Payne, M.J., Fraser, W., Lacerda, P., Bannister, M.T., Lackner, M., Chen, Y.T., Lin, H.W., Smith, K.W., Kokotanekova, R. and Young, D.,
+​                            <em> A dwarf planet class object in the 21: 5 resonance with Neptune</em>, 2018, The Astrophysical Journal Letters, 855(1), p.L6 [
+​                            <a href="Pub/Holman2018.pdf">pdf</a>]
+​                        </li><li>
+​                            Ramponi, G., Protopapas, P., Brambilla, M. and Janssen, R.,
+​                            <em> T-cgan: Conditional generative adversarial network for data augmentation in noisy time series with irregular sampling </em>, 2018, arXiv preprint arXiv:1811.08295 [
+​                            <a href="Pub/Georgia2018.pdf">pdf</a>]
+​                        </li><li>
+​                            Martínez-Palomera, J., Förster, F., Protopapas, P., Maureira, J.C., Lira, P., Cabrera-Vives, G., Huijse, P., Galbany, L., De Jaeger, T., González-Gaitán, S. and Medina, G.,
+​                            <em> The High Cadence Transit Survey (HiTS): Compilation and Characterization of Light-curve Catalogs </em>, 2018, The Astronomical Journal, 156(5), p.186. [
+​                            <a href="Pub/Jorge2018.pdf">pdf</a>]
+​                        </li><li>
+​                            Huijse, P., Estévez, P.A., Förster, F., Daniel, S.F., Connolly, A.J., Protopapas, P., Carrasco, R. and Príncipe, J.C.,
+​                            <em> Robust Period Estimation Using Mutual Information for Multiband Light Curves in the Synoptic Survey Era.
+​             The Astrophysical Journal Supplement Series</em>, 2018, 236(1), p.12 [
+​                            <a href="Pub/Pablo2018.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Belhaj, M., Protopapas, P. and Pan, W.,
+​                            <em>Deep variational transfer: Transfer learning through semi-supervised deep generative models</em>, 2018, arXiv preprint arXiv:1812.03123 [
+​                            <a href="Pub/Marouan2018.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Maat, J.R., Gianniotis, N. and Protopapas, P.,
+​                            <em> July. Efficient optimization of echo state networks for time series datasets</em>, 2018, In 2018 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE [
+​                            <a href="Pub/Reinier2018.pdf">pdf</a>]
+​                        </li><li>
+​                            Hoernle, N., Gal, K., Grosz, B., Protopapas, P. and Rubin, A.,
+​                            <em> Modeling the Effects of Students' Interactions with Immersive Simulations Using Markov Switching Systems</em>, 2018, International Educational Data Mining Society [
+​                            <a href="Pub/Nick2018.pdf">pdf</a>]
+​                        </li><li>
+​                            Martínez-Galarza, J.R., Protopapas, P., Smith, H.A. and Morales, E.F.,
+​                            <em>Unraveling the Spectral Energy Distributions of Clustered YSOs</em>, 2018, The Astrophysical Journal, 864(1), p.71. [
+​                            <a href="Pub/Rafael2018.pdf">pdf</a>]
+​                        </li><li>
+​                            Davis, R.C., Cabrera-Vives, G., Förster, F., Estévez, P.A., Huijse, P., Protopapas, P., Reyes, I., Martínez, J. and Donoso, C.,
+​                            <em>Deep Learning for Image Sequence Classification of Astronomical Events</em>, 2018, arXiv preprint arXiv:1807.03869 [
+​                            <a href="Pub/Rodrigo2018.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Jiang, Y.F., Green, P.J., Greene, J.E., Morganson, E., Shen, Y., Pancoast, A., MacLeod, C.L., Anderson, S.F., Brandt, W.N., Grier, C.J. and Rix, H.W., <em>Detection of time lags between quasar continuum emission bands based on Pan-STARRS light curves</em>,
+​                            2017, The Astrophysical Journal, 836(2), p.186 [<a href="Pub/Holman2017.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Benavente, P., Protopapas, P. and Pichara, K.,
+​                            <em>Automatic survey-invariant classification of variable stars</em>, 2017, The Astrophysical Journal, 845(2), p.147 [
+​                            <a href="Pub/Patricio2017.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Castro, N., Protopapas, P. and Pichara, K.,
+​                            <em>Uncertain classification of variable stars: handling observational GAPS and noise</em>, 2017, The Astronomical Journal, 155(1), p.16 [
+​                            <a href="Pub/Nicolas2017.pdf">pdf</a>]
+​                        </li><li>
+​                            Protopapas, P., <em>Recurrent Neural Network Applications for Astronomical Time Series</em>, 2017, In American Astronomical Society Meeting Abstracts# 230 (Vol. 230, pp. 104-03). [
+​                            <a href="Pub/Protopapas2017.pdf">pdf</a>]
+​                        </li><li>
+​                            Mackenzie, C., Pichara, K. and Protopapas, P.,
+​                            <em>Clustering-based feature learning on variable stars</em>, 2016, The Astrophysical Journal, 820(2), p.138 [
+​                            <a href="Pub/Cristobal2016.pdf">pdf</a>]
+​                        </li><li>
+​                            Pichara, K., Protopapas, P. and León, D.,
+​                            <em>Meta-classification for variable stars</em>, 2016, The Astrophysical Journal, 819(1), p.18 [
+​                            <a href="Pub/Karim2016.pdf">pdf</a>]
+​                        </li><li>
+​                            Narasimhan, H., Pan, W., Kar, P., Protopapas, P. and Ramaswamy, H.G.,
+​                            <em>December. Optimizing the multiclass F-measure via biconcave programming</em>, 2016, In 2016 IEEE 16th international conference on data mining (ICDM) (pp. 1101-1106). IEEE [
+​                            <a href="Pub/Hari2016.pdf">pdf</a>]
+​                        </li><li>
+​                            Nun, I., Protopapas, P., Sim, B. and Chen, W.,
+​                            <em>Ensemble learning method for outlier detection and its application to astronomical light curves</em> The Astronomical Journal, 152(3), p.71 [
+​                            <a href="Pub/Isadora2016.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Kim, R., <em> Empirical Methods in Peer Prediction (Doctoral dissertation) </em> [
+​                            <a href="Pub/Kim2016.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Xia, X., Protopapas, P. and Doshi-Velez, F.,
+​                            <em>Cost-Sensitive Batch Mode Active Learning: Designing Astronomical Observation by Optimizing Telescope Time and Telescope Choice</em> In Proceedings of the 2016 SIAM International Conference on Data Mining (pp. 477-485).
+​                            Society for Industrial and Applied Mathematics [
+​                            <a href="Pub/Xia2016.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Nun, I., Protopapas, P., Sim, B., Zhu, M., Dave, R., Castro, N. and Pichara, K., <em>Fats: Feature analysis for time series</em>, 2105, arXiv preprint arXiv:1506.00010 [
+​                            <a href="Pub/Isadora2015.pdf">pdf</a>]
+​                        </li><li>
+​                            Protopapas, P., Huijse, P., Estevez, P.A., Zegers, P., Principe, J.C. and Marquette, J.B.,
+​                            <em>A novel, fully automated pipeline for period estimation in the eros 2 data set</em>, 2015, The Astrophysical Journal Supplement Series, 216(2), p.25 [
+​                            <a href="Pub/Pavlos2015.pdf">pdf</a>]
+​                        </li><li>
+​                            Yang, J.J., Wang, X., Protopapas, P. and Bornn, L.,
+​                            <em>Fast and optimal nonparametric sequential design for astronomical observations</em>, 2015, arXiv preprint arXiv:1501.02467 [
+​                            <a href="Pub/Yang2015.pdf">pdf</a>]
+​                        </li><li>
+​                            Kim, D.W., Protopapas, P., Bailer-Jones, C.A., Byun, Y.I., Chang, S.W., Marquette, J.B. and Shin, M.S.,
+​                            <em>The EPOCH Project-I. Periodic variable stars in the EROS-2 LMC database</em>, 21014, Astronomy &amp; Astrophysics, 566, p.A43 [
+​                            <a href="Pub/daewon2014.pdf">pdf</a>]
+​                        </li><li>
+​                            Huijse, P., Estevez, P.A., Protopapas, P., Principe, J.C. and Zegers, P.,
+​                            <em>Computational intelligence challenges and applications on large-scale astronomical time series databases</em>, 2014, IEEE Computational Intelligence Magazine, 9(3), pp.27-39 [
+​                            <a href="Pub/Pablo2014.pdf">pdf</a>]
+​                        </li><li>
+​                            Nun, I., Pichara, K., Protopapas, P. and Kim, D.W.,
+​                            <em>Supervised detection of anomalous light curves in massive astronomical catalogs</em>, 2014 The Astrophysical Journal, 793(1), p.23 [
+​                            <a href="Pub/Isadora2014.pdf">pdf</a>]
+​                        </li><li>
+​                            Verde, L., Protopapas, P. and Jimenez, R.,
+​                            <em>The expansion rate of the intermediate universe in light of Planck</em>, 2014, Physics of the Dark Universe, 5, pp.307-314 [
+​                            <a href="Pub/Licia2014.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Verde, L., Protopapas, P. and Jimenez, R.,
+​                            <em>Planck and the local Universe: Quantifying the tension</em>, 2013, Physics of the Dark Universe, 2(3), pp.166-175 [
+​                            <a href="Pub/Licia2013.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Pichara, K. and Protopapas, P.,
+​                            <em>Automatic classification of variable stars in catalogs with missing data</em>, 2103, The Astrophysical Journal, 777(2), p.83 [
+​                            <a href="Pub/Karim2013.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Chang, S.W., Protopapas, P., Kim, D.W. and Byun, Y.I.,
+​                            <em>Statistical properties of Galactic δ Scuti stars: revisited</em>, 2013, The Astronomical Journal, 145(5), p.132 [
+​                            <a href="Pub/Daewon2013.pdf">pdf</a>]
+​                        </li><li>
+​                            Huijse, P., Estevez, P.A., Protopapas, P., Zegers, P. and Principe, J.C.,
+​                            <em>An information theoretic algorithm for finding periodicities in stellar light curves</em>, 2012, IEEE Transactions on Signal Processing, 60(10), pp.5135-5145 [
+​                            <a href="Pub/Pablo2012.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Pichara, K., Protopapas, P., Kim, D.W., Marquette, J.B. and Tisserand, P.,
+​                            <em>An improved quasar detection method in EROS-2 and MACHO LMC data sets</em>, 2012, Monthly Notices of the Royal Astronomical Society, 427(2), pp.1284-1297 [
+​                            <a href="Pub/Karim2012.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Wang, Y., Khardon, R. and Protopapas, P.,
+​                            <em>Nonparametric Bayesian estimation of periodic light curves</em> 2012, The Astrophysical Journal, 756(1), p.67 [
+​                            <a href="Pub/Roni2012.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Kim, D.W., Protopapas, P., Trichas, M., Rowan-Robinson, M., Khardon, R., Alcock, C. and Byun, Y.I.,
+​                            <em>A Refined QSO Selection Method Using Diagnostics Tests: 663 QSO Candidates in the Large Magellanic Cloud</em> The Astrophysical Journal, 747(2), p.107 [
+​                            <a href="Pub/Daewon2012.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Blocker, A.W. and Protopapas, P.,
+​                            <em>Semi-parametric robust event detection for massive time-domain databases</em>, 2012, In Statistical Challenges in Modern Astronomy V (pp. 177-187). Springer, New York, NY [
+​                            <a href="Pub/Alex2012.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Wang, Y., Khardon, R. and Protopapas, P.,
+​                            <em>Infinite shift-invariant grouped multi-task learning for gaussian processes</em>, 2012, arXiv preprint arXiv:1203.0970 [
+​                            <a href="Pub/wang2012.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Huijse, P., Estévez, P.A., Protopapas, P., Zegers, P. and Príncipe, J.C.,
+​                            <em>Computational Challenges in Processing Very Large Astronomical Survey Databases</em>, 2012, In 2012 9th Asia-Pacific Symposium on Information and Telecommunication Technologies (APSITT) (pp. 1-6). IEEE [
+​                            <a href="Pub/Pablo2012.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Kim, D.W., Protopapas, P., Byun, Y.I., Alcock, C., Khardon, R. and Trichas, M.,
+​                            <em>Quasi-stellar object selection algorithm using time variability and machine learning: Selection of 1620 quasi-stellar object candidates from MACHO Large Magellanic Cloud database</em> ,2011, The Astrophysical Journal, 735(2),
+​                            p.68 [
+​                            <a href="Pub/Daewon2011.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Huijse, P., Estévez, P.A., Zegers, P., Príncipe, J.C. and Protopapas, P.,
+​                            <em>Period estimation in astronomical time series using slotted correntropy</em>, 2011, IEEE Signal Processing Letters, 18(6), pp.371-374 [
+​                            <a href="Pub/Pablos2011.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Wang, Y., Khardon, R. and Protopapas, P.,
+​                            <em> Nonparametric Bayesian estimation of periodic functions</em> 2011, arXiv preprint arXiv:1111.1315 [
+​                            <a href="Pub/Wang2011.pdf">pdf</a>]
+
+​                        </li><li>
+​                            Mishra, B.P., Principe, J.C., Estevez, P.A. and Protopapas, P.,
+​                            <em> 2011, In 2011 IEEE International Workshop on Machine Learning for Signal Processing (pp. 1-6). IEEE [
+​                            <a href="Pub/Mishra2011.pdf">pdf</a>]
+​                        </em></li><li>
+​                            Fuentes, C.I., Holman, M.J., Trilling, D.E. and Protopapas, P.,
+​                            <em>Trans-Neptunian objects with Hubble Space Telescope ACS/WFC</em> 2011, The Astrophysical Journal, 722(2), p.1290 [
+​                            <a href="Pub/Cesar2010.pdf">pdf</a>]
+​                        </li><li>
+​                            Wang, Y., Khardon, R. and Protopapas, P.,
+​                            <em>Shift-invariant grouped multi-task learning for Gaussian processes</em>, 2010, In Joint European Conference on Machine Learning and Knowledge Discovery in Databases (pp. 418-434). Springer, Berlin, Heidelberg [
+​                            <a href="Pub/Wang2010.pdf">pdf</a>]
+​                        </li><li>
+​                            Estévez, P.A., Huijse, P., Zegers, P., Principe, J.C. and Protopapas, P.,
+​                            <em>Period detection in light curves from astronomical objects using correntropy</em>, 2010, In The 2010 International Joint Conference on Neural Networks (IJCNN) (pp. 1-7). IEEE [
+​                            <a href="Pub/Pablos2010.pdf">pdf</a>]
+​                        </li><li>
+​                            U. Rebbapragada, P. Protopapas, C. Brodley, C. Alcock, <em>Finding Anomalies in Periodic Time Series</em>, Machine Learning, p. 281, vol. 74, (<span class="style5">2009</span>) [<a href="Pub/Umaa2009.pdf">pdf</a>]</li><li>
+​                            S. Pember, C. Brodley, P. Protopapas, and A. Kilmer, <em>Similarity Retrieval in Large Datasets using Rank Revealing QR</em>, ICDM,  Under review at IEEE PAMI, (<span class="style5">2009</span>).<br/>
+​                        </li><li>
+​                            Dan Preston, Pavlos Protopapas and Carla Brodley<em>, Event Detection in Time Series</em>, Proceedings of the Ninth SIAM International Conference on Data Mining, p. 61-72, (<span class="style5">2009</span>) [<a href="Pub/prestondSIAM.pdf" target="_blank" ​="">pdf</a>]<br/>
+​                        </li><li>
+​                            Dan Preston, Pavlos Protopapas and Carla Brodley, <em>Discovering Arbitrary Event Types in Time Series,</em> SIAM Best of 09 SDM, (<span class="style5">2009</span>)<br/></li><li>
+​                            Dae-Won Kim, Pavlos Protopapas, Charles Alcock, Yong-Ik Byun, Federica Bianco<em>, Detection of Flare Stars in TAOS 2-year Data</em>, The Astronomer's Telegram, vol. #2035, (<span class="style5">2009</span>) [<a href="http://www.astronomerstelegram.org/?read=2035" target="_blank" ​="">html</a>] <br/>
+​                        </li><li>
+​                            Gabriel Wachman, Roni Khardon, Pavlos Protopapas, Charles R. Alcock, <em>Kernels for Periodic Time Series Arising in Astronomy</em>, ECML PKDD, (<span class="style5">2009</span>) [<a href="Pub/Wachman2009.pdf" target="_blank">pdf</a>]<br ​=""/>
+​                        </li><li>
+​                            Dae-Won Kim, Pavlos Protopapas, Yong-Ik Byun, Charles Alcock and the TAOS collaboration, <em>The TAOS Project Stellar Variability I. Detection of Low-Amplitude δ Scuti Stars and a Revised Catalog of All Known δ Scuti Stars,</em>                            submitted to Astronomical Journal, (<span class="style5">2009</span>) [<a href="Pub/DSC2009.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            J.~H. Wang, P.  Protopapas, W. –P. Chen, C. R. Alcock,  W. S. Burgett, T. Dombeck, J. S. Morgan, P. A. Price, J. L. Tonry, <em>Searching for sub-kilometer TNOs using Pan-STARRS video mode lightcurves:</em><strong> </strong><em>Preliminary study and evaluation using engineering data, </em>submitted
+​                            to Astronomical Journal,  (<span class="style5">2009</span>) [<a href="Pub/Wang2009.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            A. W. Blocker, P. Protopapas, C. R. Alcock<em>, A Bayesian approach to the analysis of time symmetry in light curves: Reconsidering Scorpius X-1 occultations</em>, The Astronomical Journal, Volume 138, Issue 2, pp. 568-578,
+​                            (
+​                            <span class="style5">2009</span>) [<a href="Pub/Blocker2009.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            F. Bianco, P. Protopapas, B. McLeod, C. R. Alcock,  M. J.  Holman, M. J. Lehner. <em>A Search for Occultations of Bright Stars by Small Kuiper Belt Objects using Megacam on the MMT, </em>The Astronomical Journal,
+​                            Volume 138, Issue 2, pp. 568-578, (<span class="style5">2009</span>) [<a href="Pub/Bianco2009.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            D-W Kim, P. Protopapas, C. Alcock, B. Yong-Ik, F. Bianco,  <em>De-Trending Time Series for Astronomical Variability Surveys</em>, Monthly Notices of the Royal Astronomical Society, Volume 397, Issue 2, pp. 558-568,<em> (2008)</em>                            [<a href="Pub/DaeWon-Detrend.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            R. E. Schild,  J. Lovegrove, P. Protopapas, <em>Reverberation in the UV-Optical Continuum Brightness Fluctuations of MACHO Quasar</em>, The Astronomical Journal, Volume 138, Issue 2, pp. 421-427, (<span class="style5">2009</span>)
+​                            [
+​                            <a href="Pub/Schild2009.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            Zhan et al.<strong>, </strong><em>First Results from the Taiwanese-American Occultation Survey (TAOS)</em>, ApJL, 685, L157, (<span class="style5">2008</span>) [<a href="http://arxiv.org/pdf/0808.2051v1">pdf</a>]<br/>
+​                        </li><li>
+​                            E. Morikawa, R. Dave,  P. Protopapas, <em>A Novel GUI Based Interactive Work Flow Application for Exploratory and Batch Processing of Light Curves, </em>Astronomical Data Analysis Software and Systems XVII, 394, 357, (
+​                            <span class="style5">2008)</span> [<a href="Pub/Morikawa2007.pdf">pdf</a>]<br/>
+​                        </li><li>
+​                            Lorenzo Faccioli, Charles Alcock, Kem Cook, Gabriel E. Prochter, Pavlos Protopapas, David Syphers, <em>Eclipsing Binary Stars in the Large and Small Magellanic Clouds from the MACHO Project: The Sample</em>, AJ, 134, 1963-1994,
+​                            <span class="style5">(2007) </span>[<a href="Pub/Faccioli2007.pdf">pdf</a>] <br/>
+​                        </li><li>
+​                            Holman, Matthew J.; Protopapas, P.; Tholen, D. J., <em>Searching for Solar System Wide Binaries with Pan-STARRS-1</em>, AAS, 39, 52, <span class="style5">(2007)</span><br/></li><li>
+​                            Dave, R.; Protopapas, P.; Lehner, M., <em>Virtual Astronomical Pipelines</em>, Astronomical Data Analysis Software and Systems XVI ASP Conference Series, Vol. 376, proceedings of the conference held 15-18 October in Tucson,
+​                            Arizona, USA. Edited by Richard A. Shaw, Frank Hill and David J. Bell., p.253, <span class="style5">(2006)</span> [<a href="Pub/Dave2007.pdf">pdf</a>]<br/>
+​                        </li><li>
+​                            J. M. Diego, M. Tegmark, P. Protopapas, H. B. Sadvik, <em>Combined reconstruction of weak and strong lensing data with WSLAP</em>, MNRAS, 375, 958-970, <span class="style5">(2007)</span> [<a href="Pub/Diego2007.pdf">pdf</a>]<br ​=""/>
+​                        </li><li>
+​                            Eamonn Keogh, Li Wei, Xiaopeng Xi, Michail Vlachos, Sang-Hee Lee, Pavlos Protopapas. Supporting,<em> Exact Indexing of Shapes under Rotation Invariance with Arbitrary  
+​            Representations and Distance Measures, </em>VLDB: 882-893, (<span class="style5">2006)</span> [<a href="Pub/Eamonn2008.pdf" target="_blank">pdf</a>] <br/></li><li>
+​                            P. Protopapas, J. M. Giammarco, L.  Faccioli, M. F. Struble, R. Dave , C. Alcock, <em>Finding outlier light-curves in catalogs of periodic variable stars</em>, MNRAS, 369, 677,
+​                            <span class="style5">(<em>2006)</em> </span>[<a href="Pub/Giammarco2006.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            Pavlos Protopapas, Raul Jimenez , Charles Alcock , <em>Fast identification of transits from light-curves</em>, MNRAS, 362, 460, <span class="style5">(2005)</span> [
+​                            <a href="Pub/Jimenez2005.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            J. M. Diego, H. B. Sadvik, P. Protopapas, M. Tegmark, N. Benitez, T. Broadhurst, <em>Non-parametric mass reconstruction of A1689 from strong lensing data with SLAP</em>, MNRAS, 362, 1247,
+​                            <span class="style5">(2005)</span> [<a href="Pub/Diego2005b.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            J. M. Diego, P. Protopapas, H. B. Sadvik, M. Tegmark, <em>Non-parametric inversion of strong lensing systems</em>, MNRAS, 360, 477, (<span class="style5">2005)</span> [<a href="Pub/Diego2005.pdf" target="_blank">pdf</a>]<br ​=""/>
+​                        </li><li>
+​                            A. Klein, P. Protopapas, S. G. Rohoziński, K. Starosta, <em>Kerman-Klein-Dönau-Frauendorf model for odd-odd nuclei: Formal theory</em>,  Physical Review C,  vol. 69, Issue 3, id. 034338,
+​                            <span class="style5"> (2005)</span> [<a href="Pub/PhysRevC.69.034338.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            R. D. Amado, M. Á. Halász, P. Protopapas, <em>Two Skyrmion dynamics with ω mesons</em><strong>,</strong> Physical Review D (Particles and Fields), Volume 61, Issue 7, (<span class="style5">2000)</span> [<a href="Pub/PhysRevD.61.074022.pdf" target="_blank" ​="">pdf</a>] <br/></li><li>
+​                            Y. Lu, P. Protopapas, R. D. Amado, <em>Nucleon-antinucleon interaction from the Skyrme model. II. Beyond the product ansatz</em>, Physical Review C, 57, 1983-1990, (<span class="style5">1998)</span> [<a href="Pub/PhysRevC.57.1983.pdf" target="_blank" ​="">pdf</a>] <br/></li><li>
+​                            P. Protopapas, A. Klein, <em>Possible solution of the Coriolis attenuation problem</em>, <span class="style5">(1997)</span>, Phys. Rev. C,  55, 1810-1818 [
+​                            <a href="Pub/PhysRevC.55.1810.pdf" target="_blank">pdf</a>] <br/>
+​                        </li><li>
+​                            P. Protopapas, A. Klein, <em>Derivation and assessment of strong coupling core-particle model from the Kerman-Klein-Dönau-Frauendorf theory</em>,
+​                            <span class="style5">(1997)</span><strong>, </strong>Physical Review C (Nuclear Physics), Volume 55, Issue 2, pp.699-713 [<a href="Pub/PhysRevC.55.699.pdf" target="_blank">pdf</a>] <br/>
+​                        </li><li>
+​                            P. Protopapas, A. Klein, <em>Application of the Kerman-Klein Method to the Solution of a Spherical Shell Model for a Deformed Rare-Earth Nucleus</em>,
+​                            <span class="style5">(1997)</span>,  Physical Review Letters, Volume 78, Issue 23, June 9, pp.4347-4350 [<a href="Pub/PhysRevLett.78.4347.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            P. Protopapas, A. Klein, N. R. Walet,<em> Further application of a semimicroscopic core-particle coupling method to the properties of 155,157Gd and 159Dy</em>,
+​                            <span class="style5">(1996)</span>, Physical Review C (Nuclear Physics), Volume 53, Issue 4, April pp.1655-1659 [<a href="Pub/PhysRevC.53.1655.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            P. Protopapas, A. Klein, N. R. Walet,<em> Application of a semimicroscopic core-particle coupling method to the backbending in odd deformed nuclei</em>, <span class="style5">(1996)
+​            <strong></strong></span><strong>, </strong>Physical Review C (Nuclear Physics), Volume 54, Issue 2, pp.638-645 [<a href="Pub/PhysRevC.54.638.pdf" target="_blank">pdf</a>]<br/>
+​                        </li><li>
+​                            P. Protopapas, A. Klein, N. R. Walet,<em> Calculation of the properties of the rotational bands of 155,157Gd</em>, <span class="style5">(1994), 
+​            </span>Physical Review C (Nuclear Physics), Volume 50, Issue 1, pp.245-256 [<a href="Pub/PhysRevC.50.245.pdf" target="_blank">pdf</a>] 
+​                            
+​                        </li>
                     </ul>
                 </div>
             </div>