Self-supervised learning of motion capture HY Tung, HW Tung, E Yumer, K Fragkiadaki Advances in neural information processing systems 30, 2017 | 346 | 2017 |
Generative models and model criticism via optimized maximum mean discrepancy DJ Sutherland, HY Tung, H Strathmann, S De, A Ramdas, A Smola, ... arXiv preprint arXiv:1611.04488, 2016 | 215 | 2016 |
Adversarial inverse graphics networks: Learning 2d-to-3d lifting and image-to-image translation from unpaired supervision HYF Tung, AW Harley, W Seto, K Fragkiadaki 2017 IEEE International Conference on Computer Vision (ICCV), 4364-4372, 2017 | 164 | 2017 |
Fast and guaranteed tensor decomposition via sketching Y Wang, HY Tung, AJ Smola, A Anandkumar Advances in neural information processing systems 28, 2015 | 152 | 2015 |
Soumyajit De, Aaditya Ramdas, Alex Smola, and Arthur Gretton. Generative models and model criticism via optimized maximum mean discrepancy DJ Sutherland, HY Tung, H Strathmann arXiv preprint arXiv:1611.04488 2, 2016 | 129 | 2016 |
Learning spatial common sense with geometry-aware recurrent networks HYF Tung, R Cheng, K Fragkiadaki Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 77 | 2019 |
Physion: Evaluating physical prediction from vision in humans and machines DM Bear, E Wang, D Mrowca, FJ Binder, HYF Tung, RT Pramod, ... arXiv preprint arXiv:2106.08261, 2021 | 63 | 2021 |
Effective string processing and matching for author disambiguation WS Chin, YC Juan, Y Zhuang, F Wu, HY Tung, T Yu, JP Wang, CX Chang, ... Proceedings of the 2013 KDD Cup 2013 workshop, 1-9, 2013 | 44 | 2013 |
Reward learning from narrated demonstrations HY Tung, AW Harley, LK Huang, K Fragkiadaki Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 43 | 2018 |
Fluidlab: A differentiable environment for benchmarking complex fluid manipulation Z Xian, B Zhu, Z Xu, HY Tung, A Torralba, K Fragkiadaki, C Gan arXiv preprint arXiv:2303.02346, 2023 | 34 | 2023 |
Learning from unlabelled videos using contrastive predictive neural 3d mapping AW Harley, SK Lakshmikanth, F Li, X Zhou, HYF Tung, K Fragkiadaki arXiv preprint arXiv:1906.03764, 2019 | 29* | 2019 |
Adversarial inverse graphics networks: Learning 2D-to-3D lifting and image-to-image translation from unpaired supervision HY Fish Tung, AW Harley, W Seto, K Fragkiadaki Proceedings of the IEEE International Conference on Computer Vision, 4354-4362, 2017 | 28* | 2017 |
3D-OES: Viewpoint-Invariant Object-Factorized Environment Simulators HY Fish Tung, Z Xian, M Prabhudesai, S Lal, K Fragkiadaki Conference on Robot Learning (CoRL) 2020, arXiv: 2011.06464, 2020 | 26* | 2020 |
Combination of feature engineering and ranking models for paper-author identification in KDD Cup 2013 CL Li, YC Su, TW Lin, CH Tsai, WC Chang, KH Huang, TM Kuo, SW Lin, ... Proceedings of the 2013 KDD Cup 2013 Workshop, 1-7, 2013 | 26 | 2013 |
HyperDynamics: Meta-Learning Object and Agent Dynamics with Hypernetworks Z Xian, S Lal, HY Tung, EA Platanios, K Fragkiadaki International Conference on Learning Representations (ICLR) 2021, 2021 | 23 | 2021 |
Disentangling 3D Prototypical Networks For Few-Shot Concept Learning M Prabhudesai, S Lal, D Patil, HY Tung, AW Harley, K Fragkiadaki International Conference on Learning Representations (ICLR) 2021, 2020 | 18 | 2020 |
Spectral methods for indian buffet process inference HY Tung, AJ Smola Advances in Neural Information Processing Systems 27, 2014 | 17 | 2014 |
Embodied language grounding with 3d visual feature representations M Prabhudesai, HYF Tung, SA Javed, M Sieb, AW Harley, K Fragkiadaki Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 16 | 2020 |
Embodied language grounding with implicit 3d visual feature representations M Prabhudesai, HYF Tung, SA Javed, M Sieb, AW Harley, K Fragkiadaki | 10 | 2019 |
Novel traffic signal timing adjustment strategy based on genetic algorithm HY Tung, WC Ma, TL Yu 2014 IEEE Congress on Evolutionary Computation (CEC), 2353-2360, 2014 | 10 | 2014 |