| Deep Generative Video Compression J Han, S Lombardo, C Schroers, S Mandt Conference on Neural Information Processing Systems, 2019, 9283-9294, 2019 | 61* | 2019 |
| Stein Variational Gradient Descent Without Gradient J Han, Q Liu International Conference on Machine Learning, 2018, 2018 | 50 | 2018 |
| Deep probabilistic video compression J Han, S Lombardo, C Schroers, S Mandt arxiv.org/abs/1810.02845, 2018 | 34 | 2018 |
| Disentangled Recurrent Wasserstein Autoencoder J Han, MR Min, L Han, LE Li, X Zhang International Conference on Learning Representations (ICLR) 2021, 2021 | 32 | 2021 |
| Stein Variational Adaptive Importance Sampling J Han, Q Liu The Conference on Uncertainty in Artificial Intelligence (UAI), 2017, 2017 | 31 | 2017 |
| Stein Variational Inference for Discrete Distributions J Han, F Ding, X Liu, L Torresani, J Peng, Q Liu The 23rd International Conference on Artificial Intelligence and Statistics …, 2020 | 24 | 2020 |
| Generative Principal Component Analysis Z Liu, J Liu, S Ghosh, J Han, J Scarlett International Conference on Learning Representations (ICLR) 2022, 2022 | 15 | 2022 |
| Bootstrap model aggregation for distributed statistical learning J Han, Q Liu Conference on Neural Information Processing Systems, 2016, 2016 | 13 | 2016 |
| Projected gradient descent algorithms for solving nonlinear inverse problems with generative priors Z Liu, J Han International Joint Conference on Artificial Intelligence, 2022, 2022 | 5 | 2022 |
| Robust 1-bit compressive sensing with partial Gaussian circulant matrices and generative priors Z Liu, S Ghosh, J Han, J Scarlett 2021 IEEE Information Theory Workshop (ITW), 1-6, 2021 | 4 | 2021 |
| High efficiently numerical simulation of the TDGL equation with reticular free energy in hydrogel J Han, H Zhang, Z Zhang arXiv preprint arXiv:1706.02906, 2017 | 4 | 2017 |
| NUMERICAL SIMULATION OF CONTACT LINE PROBLEMS USING PHASE FIELD MODEL H Jun https://scholarbank.nus.edu.sg/bitstream/10635/121109/1/Thesis_HAN%20JUN.pdf, 2015 | 2 | 2015 |
| Machine learning based video compression SM Mandt, C Schoers, J Han, SD Lombardo US Patent 11,544,606, 2023 | | 2023 |
| Scalable Approximate Inference and Some Applications J Han Dartmouth College, 2019 | | 2019 |
| Video Compression through Deep Bayesian Learning J Han, S Lombardo, C Schroers, S Mandt NIPS Bayesian DL Workshop, 2018, 2018 | | 2018 |
Stephan MandtAssociate Professor, University of California, IrvineVerified email at uci.edu
