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MingSun-Tse/README.md

Hi there 👋

I am an Assistant Professor at Westlake U. I did my PhD at SMILE Lab of Northeastern University (Boston, USA). Before that, I spent seven wonderful years at Zhejiang University (Hangzhou, China) to get my B.E. and M.S. degrees.

I am interested in various topics in computer vision and machine learning. My research works orbit efficient deep learning (a.k.a. model compression), spanning from the most common image classification task (GReg, Awesome-PaI, TPP) to neural style transfer (Collaborative-Distillation), single image super-resolution (ASSL, SRP), and 3D novel view synthesis (R2L, MobileR2L).

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  1. Efficient-Deep-Learning Efficient-Deep-Learning Public

    Collection of recent methods on (deep) neural network compression and acceleration.

    930 132

  2. snap-research/R2L snap-research/R2L Public

    [ECCV 2022] R2L: Distilling Neural Radiance Field to Neural Light Field for Efficient Novel View Synthesis

    Python 192 23

  3. Collaborative-Distillation Collaborative-Distillation Public

    [CVPR'20] Collaborative Distillation for Ultra-Resolution Universal Style Transfer (PyTorch)

    Python 185 23

  4. Regularization-Pruning Regularization-Pruning Public

    [ICLR'21] Neural Pruning via Growing Regularization (PyTorch)

    Python 83 23

  5. Good-DA-in-KD Good-DA-in-KD Public

    [NeurIPS'22] What Makes a "Good" Data Augmentation in Knowledge Distillation -- A Statistical Perspective

    Python 36 2

  6. ASSL ASSL Public

    [NeurIPS'21 Spotlight] Aligned Structured Sparsity Learning for Efficient Image Super-Resolution (PyTorch)

    Python 59 6