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refsStatsML.bib
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@misc{2020Betancourtdiscrete,
title = {The Discrete Adjoint Method: Efficient Derivatives for Functions of Discrete Sequences},
author = {Michael Betancourt and Charles C. Margossian and Vianey Leos-Barajas},
year = {2020},
eprint = {2002.00326},
archiveprefix = {arXiv},
primaryclass = {stat.CO}
}
@book{2020ChopinImportanceSampling,
publisher = {Springer},
series = {Springer Series in Statistics},
title = {An introduction to Sequential Monte Carlo / Nicolas Chopin, Omiros Papaspiliopoulos.},
year = {2020},
author = {Chopin, Nicolas},
address = {Cham, Switzerland},
keywords = {Monte Carlo method},
language = {eng},
booktitle = {An introduction to Sequential Monte Carlo},
edition = {1st ed. 2020.},
isbn = {3-030-47845-9}
}
@article{2021BarcelosDualSteinVarInf,
author = {Lucas Barcelos and
Alexander Lambert and
Rafael Oliveira and
Paulo Borges and
Byron Boots and
Fabio Ramos},
title = {Dual Online Stein Variational Inference for Control and Dynamics},
journal = {CoRR},
volume = {abs/2103.12890},
year = {2021},
url = {https://arxiv.org/abs/2103.12890},
eprinttype = {arXiv},
eprint = {2103.12890}
}
@inproceedings{2019RamosBayesSimDomainRandomization,
author = {Fabio Ramos and
Rafael Possas and
Dieter Fox},
title = {BayesSim: Adaptive Domain Randomization Via Probabilistic Inferencefor Robotics Simulators},
booktitle = {Robotics: Science and Systems XV, University of Freiburg, Freiburgim Breisgau, Germany, June 22-26, 2019},
year = {2019},
url = {https://doi.org/10.15607/RSS.2019.XV.029},
doi = {10.15607/RSS.2019.XV.029}
}
@inproceedings{2020PossasOnlineBayesSim,
author = {Possas, Rafael and Barcelos, Lucas and Oliveira, Rafael and Fox, Dieter and Ramos, Fabio},
booktitle = {2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
title = {Online BayesSim for Combined Simulator Parameter Inference and Policy Improvement},
year = {2020},
pages = {5445-5452},
doi = {10.1109/IROS45743.2020.9341401}
}
@book{congdon2019bayesian,
author = {Congdon, Peter D.},
title = {Bayesian Hierarchical Models: With Applications Using R, Second Edition},
edition = {2nd},
year = {2019},
publisher = {Chapman and Hall/CRC},
doi = {10.1201/9780429113352},
url = {https://doi.org/10.1201/9780429113352}
}
@article{Beck1998UpdatingMA,
title = {Updating Models and Their Uncertainties. I: Bayesian Statistical Framework},
author = {James L. Beck and Lambros S. Katafygiotis},
journal = {Journal of Engineering Mechanics-asce},
year = {1998},
volume = {124},
pages = {455-461}
}
@article{Boyali2021IdentificationOV,
title = {Identification of Vehicle Dynamics Parameters Using Simulation-based Inference},
author = {Ali Boyali and Simon Thompson and David Robert Wong},
journal = {2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)},
year = {2021},
pages = {306-312}
}
@article{Nguyen2022ModelingOI,
title = {Modeling of Industrial Robot Kinematics using a Hybrid Analytical and Statistical Approach},
author = {Vinh Nguyen and Jeremy A. Marvel},
journal = {Journal of Mechanisms and Robotics},
year = {2022}
}
@article{shammas_najjar_2018,
title = {Kinematic calibration of serial manipulators using Bayesian inference},
volume = {36},
doi = {10.1017/S0263574718000024},
number = {5},
journal = {Robotica},
publisher = {Cambridge University Press},
author = {Shammas, Elie and Najjar, Shadi},
year = {2018},
pages = {738–766}
}
@article{Gupta2014RobustCO,
title = {Robust calibration of financial models using Bayesian estimators},
author = {Alok Kumar Gupta and Christoph Reisinger},
journal = {Journal of Computational Finance},
year = {2014},
volume = {17},
pages = {3-36}
}
@article{Gavryushkina2014BayesianIO,
title = {Bayesian Inference of Sampled Ancestor Trees for Epidemiology and Fossil Calibration},
author = {Alexandra Gavryushkina and David Welch and Tanja Stadler and Alexei J. Drummond},
journal = {PLoS Computational Biology},
year = {2014},
volume = {10}
}
@article{MOKHTARI2020100621,
title = {Wind speed sensor calibration in thermal power plant using Bayesian inference},
journal = {Case Studies in Thermal Engineering},
volume = {19},
pages = {100621},
year = {2020},
issn = {2214-157X},
doi = {https://doi.org/10.1016/j.csite.2020.100621},
url = {https://www.sciencedirect.com/science/article/pii/S2214157X19305398},
author = {Ali Mokhtari and Maryam Ghodrat and Pooya {Javadpoor Langroodi} and Azadeh Shahrian},
keywords = {Thermal power plant, Cooling tower, Bayesian inference, Wind, Sensor, Data, Calibration}
}
@article{BIRRELL2021112386,
title = {Bayesian inference for calibration and validation of uniaxial reinforcing steel models},
journal = {Engineering Structures},
volume = {243},
pages = {112386},
year = {2021},
issn = {0141-0296},
doi = {https://doi.org/10.1016/j.engstruct.2021.112386},
url = {https://www.sciencedirect.com/science/article/pii/S0141029621005368},
author = {Matías Birrell and Rodrigo Astroza and José I. Restrepo and Koorosh Loftizadeh and Rodrigo Carreño and Ramiro Bazáez and Francisco Hernández},
keywords = {Reinforcing steel, Constitutive models, Bayesian estimation, Sensitivity analysis}
}
@article{PATSIALIS2020111204,
title = {Bayesian calibration of hysteretic reduced order structural models for earthquake engineering applications},
journal = {Engineering Structures},
volume = {224},
pages = {111204},
year = {2020},
issn = {0141-0296},
doi = {https://doi.org/10.1016/j.engstruct.2020.111204},
url = {https://www.sciencedirect.com/science/article/pii/S0141029620338050},
author = {Dimitrios Patsialis and Aikaterini P. Kyprioti and Alexandros A. Taflanidis},
keywords = {Reduced order model calibration, Bayesian inference, Bayesian model class selection, Hierarchical models, Seismic risk assessment}
}
@article{WARNER20131,
title = {Stochastic reduced order models for random vectors: Application to random eigenvalue problems},
journal = {Probabilistic Engineering Mechanics},
volume = {31},
pages = {1-11},
year = {2013},
issn = {0266-8920},
doi = {https://doi.org/10.1016/j.probengmech.2012.07.001},
url = {https://www.sciencedirect.com/science/article/pii/S0266892012000422},
author = {James E. Warner and Mircea Grigoriu and Wilkins Aquino},
keywords = {Stochastic reduced order models, Uncertainty quantification, Random eigenvalue problem, Modal frequencies, Uncertain dynamic systems}
}
@article{Warner2015-uc,
title = {Stochastic reduced order models for inverse problems under
uncertainty},
author = {Warner, James E and Aquino, Wilkins and Grigoriu, Mircea D},
journal = {Comput Methods Appl Mech Eng},
volume = {285},
pages = {488--514},
month = {mar},
year = {2015},
doi = {10.1016/j.cma.2014.11.021},
address = {Netherlands},
keywords = {Stochastic inverse problems; material identification; stochastic
optimization; stochastic reduced order models; uncertainty
quantification}
}
@inbook{Villani2009,
author = {C{\'e}dric Villani},
title = {The Wasserstein Distances},
booktitle = {Optimal Transport: Old and New},
year = {2009},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
pages = {93--111},
isbn = {978-3-540-71050-9},
doi = {10.1007/978-3-540-71050-9_6},
url = {https://doi.org/10.1007/978-3-540-71050-9}
}
@article{huzaifaBayesianJCND2023,
title = {Using a {B}ayesian-inference approach to calibrating models for simulation in robotics},
author = {Unjhawala, H. and Zhang, R. and Hu, W. and Wu, J. and Serban, R. and Negrut, D.},
journal = {Journal of Computational and Nonlinear Dynamics},
doi = {10.1115/1.4062199},
url = {https://doi.org/10.1115/1.4062199},
volume = {18},
number = {6},
year = {2023},
month = {04},
note = {061004},
issn = {1555-1415}
}
@article{Dimov2010,
author = {I. Dimov and R. Georgieva},
title = {Monte {C}arlo algorithms for evaluating {S}obol' sensitivity indices},
journal = {Mathematics and Computers in Simulation},
volume = {81},
number = {3},
pages = {506-514},
year = {2010},
issn = {0378-4754},
doi = {https://doi.org/10.1016/j.matcom.2009.09.005},
url = {https://www.sciencedirect.com/science/article/pii/S0378475409002936}
}
@misc{robertMH2015,
title = {The {M}etropolis-{H}astings algorithm},
author = {Robert, Christian P.},
doi = {10.48550/ARXIV.1504.01896},
url = {https://arxiv.org/abs/1504.01896},
publisher = {arXiv},
year = {2015}
}
@article{kennedyOHaganBayesian2001,
title = {Bayesian calibration of computer models},
author = {Kennedy, Marc C and O'Hagan, Anthony},
journal = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
volume = {63},
number = {3},
pages = {425--464},
year = {2001},
publisher = {Wiley Online Library}
}
@article{sensitivityBorgonovo2016,
title = {Sensitivity analysis: a review of recent advances},
author = {Borgonovo, Emanuele and Plischke, Elmar},
journal = {European Journal of Operational Research},
volume = {248},
number = {3},
pages = {869--887},
year = {2016},
publisher = {Elsevier}
}
@article{heltonLatinHyper2003,
title = {Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems},
author = {Helton, Jon C and Davis, Freddie Joe},
journal = {Reliability Engineering \& System Safety},
volume = {81},
number = {1},
pages = {23--69},
year = {2003},
publisher = {Elsevier}
}
@article{nutMCMC-Hoffman2014,
title = {The {No-U-Turn} sampler: adaptively setting path lengths in {Hamiltonian Monte Carlo}.},
author = {Hoffman, Matthew D and Gelman, Andrew},
journal = {J. Mach. Learn. Res.},
volume = {15},
number = {1},
pages = {1593--1623},
year = {2014}
}
@article{Schulman2017PPO,
author = {John Schulman and
Filip Wolski and
Prafulla Dhariwal and
Alec Radford and
Oleg Klimov},
title = {Proximal Policy Optimization Algorithms},
journal = {CoRR},
volume = {abs/1707.06347},
year = {2017},
url = {http://arxiv.org/abs/1707.06347},
archiveprefix = {arXiv},
eprint = {1707.06347},
timestamp = {Mon, 13 Aug 2018 16:47:34 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/SchulmanWDRK17},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{Heess2017,
author = {Nicolas Heess and
Dhruva TB and
Srinivasan Sriram and
Jay Lemmon and
Josh Merel and
Greg Wayne and
Yuval Tassa and
Tom Erez and
Ziyu Wang and
S. M. Ali Eslami and
Martin A. Riedmiller and
David Silver},
title = {Emergence of Locomotion Behaviours in Rich Environments},
journal = {CoRR},
volume = {abs/1707.02286},
year = {2017},
url = {http://arxiv.org/abs/1707.02286},
archiveprefix = {arXiv},
eprint = {1707.02286},
timestamp = {Mon, 13 Aug 2018 16:47:47 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/HeessTSLMWTEWER17},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@book{SuttonBarto1998RL,
author = {Sutton, Richard S. and Barto, Andrew G.},
title = {Introduction to Reinforcement Learning},
year = {1998},
isbn = {0262193981},
edition = {1st},
publisher = {MIT Press},
address = {Cambridge, MA, USA}
}
@book{sutton-barto-RL2018,
title={Reinforcement learning: An introduction},
author={Sutton, Richard S and Barto, Andrew G},
year={2018},
publisher={MIT press}
}
@inproceedings{Kakade02approximatelyoptimal,
author = {Sham Kakade and John Langford},
title = {Approximately Optimal Approximate Reinforcement Learning},
booktitle = {IN PROC. 19TH INTERNATIONAL CONFERENCE ON MACHINE LEARNING},
year = {2002},
pages = {267--274},
publisher = {}
}
@article{Schulman15TRPO,
author = {John Schulman and
Sergey Levine and
Philipp Moritz and
Michael I. Jordan and
Pieter Abbeel},
title = {Trust Region Policy Optimization},
journal = {CoRR},
volume = {abs/1502.05477},
year = {2015},
url = {http://arxiv.org/abs/1502.05477},
archiveprefix = {arXiv},
eprint = {1502.05477},
timestamp = {Mon, 13 Aug 2018 16:48:08 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/SchulmanLMJA15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{Schulman15GAE,
author = {John Schulman and
Philipp Moritz and
Sergey Levine and
Michael I. Jordan and
Pieter Abbeel},
title = {High-Dimensional Continuous Control Using Generalized Advantage Estimation},
journal = {CoRR},
volume = {abs/1506.02438},
year = {2015},
url = {http://arxiv.org/abs/1506.02438},
archiveprefix = {arXiv},
eprint = {1506.02438},
timestamp = {Mon, 13 Aug 2018 16:46:51 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/SchulmanMLJA15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inbook{LeCun12BackProp,
author = {LeCun, Yann A.
and Bottou, L{\'e}on
and Orr, Genevieve B.
and M{\"u}ller, Klaus-Robert},
editor = {Montavon, Gr{\'e}goire
and Orr, Genevi{\`e}ve B.
and M{\"u}ller, Klaus-Robert},
title = {Efficient BackProp},
booktitle = {Neural Networks: Tricks of the Trade: Second Edition},
year = {2012},
publisher = {Springer Berlin Heidelberg},
address = {Berlin, Heidelberg},
pages = {9--48},
abstract = {The convergence of back-propagation learning is analyzed so as to explain common phenomenon observed by practitioners. Many undesirable behaviors of backprop can be avoided with tricks that are rarely exposed in serious technical publications. This paper gives some of those tricks, and offers explanations of why they work.},
isbn = {978-3-642-35289-8},
doi = {10.1007/978-3-642-35289-8_3},
url = {https://doi.org/10.1007/978-3-642-35289-8_3}
}
@article{Mnih13,
author = {Volodymyr Mnih and
Koray Kavukcuoglu and
David Silver and
Alex Graves and
Ioannis Antonoglou and
Daan Wierstra and
Martin A. Riedmiller},
title = {Playing Atari with Deep Reinforcement Learning},
journal = {CoRR},
volume = {abs/1312.5602},
year = {2013},
url = {http://arxiv.org/abs/1312.5602},
archiveprefix = {arXiv},
eprint = {1312.5602},
timestamp = {Mon, 13 Aug 2018 16:47:42 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/MnihKSGAWR13},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{LevineFDA15,
author = {Sergey Levine and
Chelsea Finn and
Trevor Darrell and
Pieter Abbeel},
title = {End-to-End Training of Deep Visuomotor Policies},
journal = {CoRR},
volume = {abs/1504.00702},
year = {2015},
url = {http://arxiv.org/abs/1504.00702},
archiveprefix = {arXiv},
eprint = {1504.00702},
timestamp = {Mon, 13 Aug 2018 16:47:04 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/LevineFDA15},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{Berseth18,
author = {Glen Berseth and
Cheng Xie and
Paul Cernek and
Michiel van de Panne},
title = {Progressive Reinforcement Learning with Distillation for Multi-Skilled
Motion Control},
journal = {CoRR},
volume = {abs/1802.04765},
year = {2018},
url = {http://arxiv.org/abs/1802.04765},
archiveprefix = {arXiv},
eprint = {1802.04765},
timestamp = {Mon, 13 Aug 2018 16:48:42 +0200},
biburl = {https://dblp.org/rec/bib/journals/corr/abs-1802-04765},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@book{DeepLearning_Goodfellow,
author = {Goodfellow, Ian and Bengio, Yoshua and Courville, Aaron},
title = {Deep Learning},
year = {2016},
isbn = {0262035618},
publisher = {The MIT Press}
}
@article{HORNIK1993,
title = {Some new results on neural network approximation},
journal = {Neural Networks},
volume = {6},
number = {8},
pages = {1069 - 1072},
year = {1993},
issn = {0893-6080},
doi = {https://doi.org/10.1016/S0893-6080(09)80018-X},
url = {http://www.sciencedirect.com/science/article/pii/S089360800980018X},
author = {K. Hornik}
}
@article{jones1998efficient,
title = {Efficient global optimization of expensive black-box functions},
author = {Jones, Donald R and Schonlau, Matthias and Welch, William J},
journal = {Journal of Global optimization},
volume = {13},
number = {4},
pages = {455--492},
year = {1998},
publisher = {Springer}
}
@article{Wolpert96,
author = {Wolpert, David and Macready, William},
year = {1996},
month = {03},
pages = {},
title = {No Free Lunch Theorems for Search}
}
@misc{tensorflow2015-whitepaper,
title = {{TensorFlow}: Large-Scale Machine Learning on Heterogeneous Systems},
url = {http://tensorflow.org/},
note = {Software available from tensorflow.org},
author = {
Mart\'{\i}n~Abadi and
Ashish~Agarwal and
Paul~Barham and
Eugene~Brevdo and
Zhifeng~Chen and
Craig~Citro and
Greg~S.~Corrado and
Andy~Davis and
Jeffrey~Dean and
Matthieu~Devin and
Sanjay~Ghemawat and
Ian~Goodfellow and
Andrew~Harp and
Geoffrey~Irving and
Michael~Isard and
Yangqing Jia and
Rafal~Jozefowicz and
Lukasz~Kaiser and
Manjunath~Kudlur and
Josh~Levenberg and
Dan~Man\'{e} and
Rajat~Monga and
Sherry~Moore and
Derek~Murray and
Chris~Olah and
Mike~Schuster and
Jonathon~Shlens and
Benoit~Steiner and
Ilya~Sutskever and
Kunal~Talwar and
Paul~Tucker and
Vincent~Vanhoucke and
Vijay~Vasudevan and
Fernanda~Vi\'{e}gas and
Oriol~Vinyals and
Pete~Warden and
Martin~Wattenberg and
Martin~Wicke and
Yuan~Yu and
Xiaoqiang~Zheng},
year = {2015}
}
@article{Huaiqin2009,
author = {Wu, Huaiqin},
year = {2009},
month = {09},
pages = {3432-3441},
title = {Global stability analysis of a general class of discontinuous neural networks with linear growth activation functions},
volume = {179},
journal = {Inf. Sci.},
doi = {10.1016/j.ins.2009.06.006}
}
@article{Krizhevsky2012,
author = {Krizhevsky, Alex and Sutskever, Ilya and Hinton, Geoffrey},
year = {2012},
month = {01},
pages = {},
title = {ImageNet Classification with Deep Convolutional Neural Networks},
volume = {25},
journal = {Neural Information Processing Systems},
doi = {10.1145/3065386}
}
@inproceedings{zhu2018reinforcement,
title = {Reinforcement and Imitation Learning for Diverse Visuomotor Skills},
author = {Yuke Zhu and Ziyu Wang and Josh Merel and Andrei Rusu and Tom Erez and Serkan Cabi and Saran Tunyasuvunakool and J\'anos Kram\'ar and Raia Hadsell and Nando de Freitas and Nicolas Heess},
booktitle = {Robotics: Science and Systems},
year = {2018}
}
@article{Amini2020RLDriving,
author = {A. {Amini} and I. {Gilitschenski} and J. {Phillips} and J. {Moseyko} and R. {Banerjee} and S. {Karaman} and D. {Rus}},
journal = {IEEE Robotics and Automation Letters},
title = {Learning Robust Control Policies for End-to-End Autonomous Driving From Data-Driven Simulation},
year = {2020},
volume = {5},
number = {2},
pages = {1143-1150}
}
@article{bayarriDataDrivenGM2007,
title = {A framework for validation of computer models},
author = {Bayarri, Maria J and Berger, James O and Paulo, Rui and Sacks, Jerry and Cafeo, John A and Cavendish, James and Lin, Chin-Hsu and Tu, Jian},
journal = {Technometrics},
volume = {49},
number = {2},
pages = {138--154},
year = {2007},
publisher = {Taylor \& Francis}
}
@book{parameterEstimation2018,
title = {Parameter estimation and inverse problems},
author = {Aster, Richard C and Borchers, Brian and Thurber, Clifford H},
year = {2018},
publisher = {Elsevier}
}
@article{YurongALDriving17,
author = {Yurong You and
Xinlei Pan and
Ziyan Wang and
Cewu Lu},
title = {Virtual to Real Reinforcement Learning for Autonomous Driving},
journal = {CoRR},
volume = {abs/1704.03952},
year = {2017},
url = {http://arxiv.org/abs/1704.03952},
archiveprefix = {arXiv},
eprint = {1704.03952},
timestamp = {Mon, 13 Aug 2018 16:49:09 +0200},
biburl = {https://dblp.org/rec/journals/corr/YouPWL17.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{benSurveyMultifiedlity2018,
title = {Survey of multifidelity methods in uncertainty propagation, inference, and optimization},
author = {Peherstorfer, Benjamin and Willcox, Karen and Gunzburger, Max},
journal = {SIAM Review},
volume = {60},
number = {3},
pages = {550--591},
year = {2018},
publisher = {SIAM}
}
@article{saltelliSensitivity2010,
title = {Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index},
author = {Saltelli, Andrea and Annoni, Paola and Azzini, Ivano and Campolongo, Francesca and Ratto, Marco and Tarantola, Stefano},
journal = {Computer physics communications},
volume = {181},
number = {2},
pages = {259--270},
year = {2010},
publisher = {Elsevier}
}
@article{kennedyOHaganBayesCalibration2001,
title = {Bayesian calibration of computer models},
author = {Marc C. Kennedy, Anthony O'Hagan},
journal = {Journal of the Royal Statistical Society},
volume = {63},
number = {3},
pages = {425--464},
year = {2001}
}
@article{kennedy2000prediction,
issn = {00063444},
url = {http://www.jstor.org/stable/2673557},
author = {M. C. Kennedy and A. O'Hagan},
journal = {Biometrika},
number = {1},
pages = {1--13},
publisher = {[Oxford University Press, Biometrika Trust]},
title = {Predicting the Output from a Complex Computer Code When Fast Approximations Are Available},
volume = {87},
year = {2000}
}
# this is highly cited
@article{engleAutoregressive1982,
title = {Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation},
author = {Engle, Robert F},
journal = {Econometrica: Journal of the econometric society},
pages = {987--1007},
year = {1982},
publisher = {JSTOR}
}
# this is highly cited
@article{bollerslevGARCH1986,
title = {Generalized autoregressive conditional heteroskedasticity},
author = {Bollerslev, Tim},
journal = {Journal of Econometrics},
volume = {31},
number = {3},
pages = {307--327},
year = {1986},
publisher = {Elsevier}
}
@article{kimStochasticVolatility1998,
title = {Stochastic volatility: likelihood inference and comparison with ARCH models},
author = {Kim, Sangjoon and Shephard, Neil and Chib, Siddhartha},
journal = {The Review of Economic Studies},
volume = {65},
number = {3},
pages = {361--393},
year = {1998},
publisher = {Wiley-Blackwell}
}
@article{hosszejniStatisticsSoftware2021,
title = {Modeling Univariate and Multivariate Stochastic Volatility in R with stochvol and factorstochvol},
volume = {100},
url = {https://www.jstatsoft.org/index.php/jss/article/view/v100i12},
doi = {10.18637/jss.v100.i12},
number = {12},
journal = {Journal of Statistical Software},
author = {Hosszejni, Darjus and Kastner, Gregor},
year = {2021},
pages = {1–34}
}
@article{michaudStatisticsSoftware2021,
title = {Sequential Monte Carlo Methods in the nimble and nimbleSMC R Packages},
volume = {100},
url = {https://www.jstatsoft.org/index.php/jss/article/view/v100i03},
doi = {10.18637/jss.v100.i03},
number = {3},
journal = {Journal of Statistical Software},
author = {Michaud, Nicholas and de Valpine, Perry and Turek, Daniel and Paciorek, Christopher J. and Nguyen, Dao},
year = {2021},
pages = {1–39}
}
@article{neilShephardAPF1999,
title = {Filtering via simulation: Auxiliary particle filters},
author = {Pitt, Michael K and Shephard, Neil},
journal = {Journal of the American statistical association},
volume = {94},
number = {446},
pages = {590--599},
year = {1999},
publisher = {Taylor \& Francis}
}
@article{heltonLatinHybercube2003,
title = {Latin hypercube sampling and the propagation of uncertainty in analyses of complex systems},
author = {Helton, Jon C and Davis, Freddie Joe},
journal = {Reliability Engineering \& System Safety},
volume = {81},
number = {1},
pages = {23--69},
year = {2003},
publisher = {Elsevier}
}
@article{heltonSurveyUQ2006,
title = {Survey of sampling-based methods for uncertainty and sensitivity analysis},
author = {Helton, Jon C and Johnson, Jay Dean and Sallaberry, Cedric J and Storlie, Curt B},
journal = {Reliability Engineering \& System Safety},
volume = {91},
number = {10-11},
pages = {1175--1209},
year = {2006},
publisher = {Elsevier}
}
@article{andrieu2003introduction,
title = {An introduction to {MCMC} for machine learning},
author = {Andrieu, Christophe and De Freitas, Nando and Doucet, Arnaud and Jordan, Michael I},
journal = {Machine learning},
volume = {50},
number = {1},
pages = {5--43},
year = {2003},
publisher = {Springer}
}
@incollection{neal2011mcmc,
author = {Neal, Radford},
title = {{MCMC} using {Hamiltonian} dynamics},
editor = {Steve Brooks and Andrew Gelman and Galin Jones and Xiao-Li Meng},
booktitle = {Handbook of {M}arkov chain {M}onte {C}arlo},
publisher = {Chapman and {H}all/{CRC}},
doi = {10.1201/b10905},
year = 2011
}
@article{pymc3,
title = {Probabilistic programming in {P}ython using {PyMC3}},
author = {Salvatier, John and Wiecki, Thomas V and Fonnesbeck, Christopher},
journal = {PeerJ Computer Science},
volume = {2},
pages = {e55},
year = {2016},
publisher = {PeerJ Inc.}
}
@article{scikit-optimize,
title = {scikit-optimize/scikit-optimize: v0.9.0. {Zenodo}.},
author = {Head, Tim and Kumar, Manoj and Nahrstaedt, Holger and Louppe, Gilles and Shcherbatyi, Iaroslav},
year = {2021},
doi = {10.5281/zenodo.5565057}
}
@article{foreman2013emcee,
title = {emcee: the {MCMC} hammer},
author = {Foreman-Mackey, Daniel and Hogg, David W and Lang, Dustin and Goodman, Jonathan},
journal = {Publications of the Astronomical Society of the Pacific},
volume = {125},
number = {925},
pages = {306},
year = {2013},
publisher = {IOP Publishing}
}
@article{galbally2010non,
title = {Non-linear model reduction for uncertainty quantification in large-scale inverse problems},
author = {Galbally, David and Fidkowski, Krzysztof and Willcox, Karen and Ghattas, Omar},
journal = {International journal for numerical methods in engineering},
volume = {81},
number = {12},
pages = {1581--1608},
year = {2010},
publisher = {Wiley Online Library}
}
@article{cleary2021calibrate,
title = {Calibrate, emulate, sample},
author = {Cleary, Emmet and Garbuno-Inigo, Alfredo and Lan, Shiwei and Schneider, Tapio and Stuart, Andrew M},
journal = {Journal of Computational Physics},
volume = {424},
pages = {109716},
year = {2021},
publisher = {Elsevier}
}
@article{mockus1978application,
title = {The application of {B}ayesian methods for seeking the extremum},
author = {Mockus, Jonas and Tiesis, Vytautas and Zilinskas, Antanas},
journal = {Towards global optimization},
volume = {2},
number = {117-129},
pages = {2},
year = {1978}
}
@article{snoek2012practical,
title = {Practical {Bayesian} optimization of machine learning algorithms},
author = {Snoek, Jasper and Larochelle, Hugo and Adams, Ryan P},
journal = {Advances in neural information processing systems},
volume = {25},
year = {2012}
}
@article{shahriari2015taking,
title = {Taking the human out of the loop: A review of {Bayesian} optimization},
author = {Shahriari, Bobak and Swersky, Kevin and Wang, Ziyu and Adams, Ryan P and De Freitas, Nando},
journal = {Proceedings of the IEEE},
volume = {104},
number = {1},
pages = {148--175},
year = {2015},
publisher = {IEEE}
}
@article{neal2001annealed,
title = {Annealed importance sampling},
author = {Neal, Radford M},
journal = {Statistics and computing},
volume = {11},
number = {2},
pages = {125--139},
year = {2001},
publisher = {Springer}
}
@incollection{doucet2001introduction,
title = {An introduction to sequential {Monte Carlo} methods},
author = {Doucet, Arnaud and Freitas, Nando de and Gordon, Neil},
booktitle = {Sequential Monte Carlo methods in practice},
pages = {3--14},
year = {2001},
publisher = {Springer}
}
@article{del2006sequential,
title = {Sequential {Monte Carlo} samplers},
author = {Del Moral, Pierre and Doucet, Arnaud and Jasra, Ajay},
journal = {Journal of the Royal Statistical Society: Series B (Statistical Methodology)},
volume = {68},
number = {3},
pages = {411--436},
year = {2006},
publisher = {Wiley Online Library}
}
@book{williams2006gaussian,
title = {Gaussian processes for machine learning},
author = {Williams, Christopher K and Rasmussen, Carl Edward},
volume = {2},
number = {3},
year = {2006},
publisher = {MIT press Cambridge, MA}
}
@article{arviz2019,
doi = {10.21105/joss.01143},
url = {https://doi.org/10.21105/joss.01143},
year = {2019},
publisher = {The Open Journal},
volume = {4},
number = {33},
pages = {1143},
author = {Ravin Kumar and Colin Carroll and Ari Hartikainen and Osvaldo Martin},
title = {{ArviZ}: a unified library for exploratory analysis of {B}ayesian models in {P}ython},
journal = {Journal of Open Source Software}
}
@article{Vehtari2021,
doi = {10.1214/20-ba1221},
url = {https://doi.org/10.1214%2F20-ba1221},
year = 2021,
month = {jun},
publisher = {Institute of Mathematical Statistics},
volume = {16},
number = {2},
author = {Aki Vehtari and Andrew Gelman and Daniel Simpson and Bob Carpenter and Paul-Christian Bürkner},
title = {Rank-Normalization, Folding, and Localization: An Improved {$\hat{R}$} for Assessing Convergence of {MCMC} (with Discussion)},
journal = {Bayesian Analysis}
}
@article{stanCarpenter2017,
title = {{STAN}: A Probabilistic Programming Language for Bayesian Inference and Optimization},
author = {Bob Carpenter and Andrew Gelman and Matthew Hoffman and Daniel Lee and Ben Goodrich and Michael Betancourt and Marcus Brubaker and Jiqiang Guo and Peter Li and Allen Riddell},
journal = {Journal of Statistical Software},
volume = {76},
number = {1},
pages = {1--32},
year = {2017},
publisher = {Foundation for Open Access Statistics},
doi = {10.18637/jss.v076.i01},
url = {https://www.jstatsoft.org/article/view/v076i01}
}
@book{baysianTutorialKruschke2014,
title = {Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan},
author = {John K. Kruschke},
year = {2014},
edition = {2nd},
publisher = {Academic Press},
address = {San Diego, CA},
isbn = {978-0124058880}
}
@article{gelman2015,
title={Stan: A probabilistic programming language for Bayesian inference and optimization},
author={Gelman, Andrew and Lee, Daniel and Guo, Jiqiang},
journal={Journal of Educational and Behavioral Statistics},
volume={40},
number={5},
pages={530--543},
year={2015},
publisher={Sage Publications Sage CA: Los Angeles, CA}
}
@book{gelmanBayesian1995,
title = {Bayesian data analysis},
author = {Gelman, Andrew and Carlin, John B and Stern, Hal S and Rubin, Donald B},
year = {1995},
publisher = {Chapman and Hall/CRC}
}
@article{Gelman1992,
author = {Andrew Gelman and Donald B. Rubin},
title = {Inference from Iterative Simulation Using Multiple Sequences},
volume = {7},
journal = {Statistical Science},
number = {4},
publisher = {Institute of Mathematical Statistics},
pages = {457 -- 472},
keywords = {Bayesian inference, Convergence of stochastic processes, ECM, EM, Gibbs sampler, importance sampling, Metropolis algorithm, multiple imputation, random-effects model, SIR},
year = {1992},
doi = {10.1214/ss/1177011136},
url = {https://doi.org/10.1214/ss/1177011136}
}
@article{Flegal2008,
author = {James M. Flegal and Murali Haran and Galin L. Jones},
title = {{Markov chain Monte Carlo}: Can We Trust the Third Significant Figure?},
volume = {23},
journal = {Statistical Science},
number = {2},
publisher = {Institute of Mathematical Statistics},
pages = {250 -- 260},
keywords = {Convergence diagnostic, Markov chain, Monte Carlo, standard errors},
year = {2008},
doi = {10.1214/08-STS257},
url = {https://doi.org/10.1214/08-STS257}
}
@book{robert1999monte,
title = {Monte Carlo statistical methods},
author = {Robert, Christian P and Casella, George and Casella, George},
volume = {2},
year = {1999},
publisher = {Springer}
}