| Alternating back-propagation for generator network T Han, Y Lu, SC Zhu, YN Wu Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 139 | 2017 |
| On the anatomy of mcmc-based maximum likelihood learning of energy-based models E Nijkamp, M Hill, T Han, SC Zhu, YN Wu Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 5272-5280, 2020 | 122 | 2020 |
| Learning latent space energy-based prior model B Pang, T Han, E Nijkamp, SC Zhu, YN Wu Advances in Neural Information Processing Systems 33, 21994-22008, 2020 | 97 | 2020 |
| Survey on person re‐identification based on deep learning K Wang, H Wang, M Liu, X Xing, T Han CAAI Transactions on Intelligence Technology 3 (4), 219-227, 2018 | 63 | 2018 |
| Divergence triangle for joint training of generator model, energy-based model, and inferential model T Han, E Nijkamp, X Fang, M Hill, SC Zhu, YN Wu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 56 | 2019 |
| Learning multi-layer latent variable model via variational optimization of short run mcmc for approximate inference E Nijkamp, B Pang, T Han, L Zhou, SC Zhu, YN Wu Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 36 | 2020 |
| Parsing façade with rank-one approximation C Yang, T Han, L Quan, CL Tai 2012 IEEE Conference on Computer Vision and Pattern Recognition, 1720-1727, 2012 | 35 | 2012 |
| Joint training of variational auto-encoder and latent energy-based model T Han, E Nijkamp, L Zhou, B Pang, SC Zhu, YN Wu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 34 | 2020 |
| Unsupervised disentangling of appearance and geometry by deformable generator network X Xing, T Han, R Gao, SC Zhu, YN Wu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 32 | 2019 |
| Deformable generator networks: unsupervised disentanglement of appearance and geometry X Xing, R Gao, T Han, SC Zhu, YN Wu IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (3), 1162-1179, 2020 | 28 | 2020 |
| A tale of three probabilistic families: Discriminative, descriptive, and generative models YN Wu, R Gao, T Han, SC Zhu Quarterly of Applied Mathematics 77 (2), 423-465, 2019 | 21 | 2019 |
| Neuro-symbolic program search for autonomous driving decision module design J Sun, H Sun, T Han, B Zhou Conference on Robot Learning, 21-30, 2021 | 18 | 2021 |
| Star: Sparse transformer-based action recognition F Shi, C Lee, L Qiu, Y Zhao, T Shen, S Muralidhar, T Han, SC Zhu, ... arXiv preprint arXiv:2107.07089, 2021 | 18 | 2021 |
| Lavs: A lightweight audio-visual saliency prediction model D Zhu, D Zhao, X Min, T Han, Q Zhou, S Yu, Y Chen, G Zhai, X Yang 2021 IEEE International Conference on Multimedia and Expo (ICME), 1-6, 2021 | 10 | 2021 |
| Learning generator networks for dynamic patterns T Han, Y Lu, J Wu, X Xing, YN Wu 2019 IEEE Winter Conference on Applications of Computer Vision (WACV), 809-818, 2019 | 10 | 2019 |
| Learning latent space energy-based prior model for molecule generation B Pang, T Han, YN Wu arXiv preprint arXiv:2010.09351, 2020 | 9 | 2020 |
| Semi-supervised learning by latent space energy-based model of symbol-vector coupling B Pang, E Nijkamp, J Cui, T Han, YN Wu arXiv preprint arXiv:2010.09359, 2020 | 7 | 2020 |
| Learning multi-view generator network for shared representation T Han, X Xing, YN Wu 2018 24th International Conference on Pattern Recognition (ICPR), 2062-2068, 2018 | 7 | 2018 |
| Towards multi-scale deep features learning with correlation metric for person re-identification D Zhu, Q Zhou, T Han, Y Chen, D Zhao, X Yang Knowledge-Based Systems 213, 106675, 2021 | 6 | 2021 |
| Quasi-regular facade structure extraction T Han, C Liu, CL Tai, L Quan Computer Vision–ACCV 2012: 11th Asian Conference on Computer Vision, Daejeon …, 2013 | 6 | 2013 |
Ying Nian WuUCLA Department of StatisticsVerified email at stat.ucla.edu
