| Implicit generation and generalization in energy-based models Y Du, I Mordatch arXiv preprint arXiv:1903.08689, 2019 | 278* | 2019 |
| Observational overfitting in reinforcement learning X Song, Y Jiang, S Tu, Y Du, B Neyshabur arXiv preprint arXiv:1912.02975, 2019 | 64 | 2019 |
| Neural MMO: A massively multiagent game environment for training and evaluating intelligent agents J Suarez, Y Du, P Isola, I Mordatch arXiv preprint arXiv:1903.00784, 2019 | 42* | 2019 |
| Neural radiance flow for 4d view synthesis and video processing Y Du, Y Zhang, HX Yu, JB Tenenbaum, J Wu 2021 IEEE/CVF International Conference on Computer Vision (ICCV), 14304-14314, 2021 | 40 | 2021 |
| Task-agnostic dynamics priors for deep reinforcement learning Y Du, K Narasimhan International Conference on Machine Learning, 1696-1705, 2019 | 35 | 2019 |
| Improved contrastive divergence training of energy based models Y Du, S Li, J Tenenbaum, I Mordatch arXiv preprint arXiv:2012.01316, 2020 | 31 | 2020 |
| Energy-based models for atomic-resolution protein conformations Y Du, J Meier, J Ma, R Fergus, A Rives arXiv preprint arXiv:2004.13167, 2020 | 31 | 2020 |
| 3d shape generation and completion through point-voxel diffusion L Zhou, Y Du, J Wu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 26 | 2021 |
| Learning to exploit stability for 3d scene parsing Y Du, Z Liu, H Basevi, A Leonardis, B Freeman, J Tenenbaum, J Wu Advances in Neural Information Processing Systems 31, 2018 | 25 | 2018 |
| Compositional visual generation with energy based models Y Du, S Li, I Mordatch Advances in Neural Information Processing Systems 33, 6637-6647, 2020 | 22* | 2020 |
| Model Based planning with energy-based models Y Du, T Lin, I Mordatch arXiv preprint arXiv:1909.06878, 2019 | 22* | 2019 |
| Learning to plan with pointcloud affordances for general-purpose dexterous manipulation A Simeonov, Y Du, B Kim, FR Hogan, P Agrawal, A Rodriguez Conference on Robot Learning, 2020 | 13* | 2020 |
| Energy-Based Models for Continual Learning S Li, Y Du, GM van de Ven, I Mordatch arXiv preprint arXiv:2011.12216, 2020 | 12 | 2020 |
| Unsupervised discovery of 3d physical objects from video Y Du, K Smith, T Ulman, J Tenenbaum, J Wu arXiv preprint arXiv:2007.12348, 2020 | 12 | 2020 |
| An empirical study on hyperparameters and their interdependence for RL generalization X Song, Y Du, J Jackson arXiv preprint arXiv:1906.00431, 2019 | 9 | 2019 |
| Learning to Compose Visual Relations N Liu*, S Li*, Y Du*, J Tenenbaum, A Torralba Advances in Neural Information Processing Systems 34, 2021 | 6 | 2021 |
| Unsupervised learning of compositional energy concepts Y Du, S Li, Y Sharma, J Tenenbaum, I Mordatch Advances in Neural Information Processing Systems 34, 15608-15620, 2021 | 6 | 2021 |
| Yilun Du, Clare Zhu, Igor Mordatch, and Phillip Isola. The neural mmo platform for massively multiagent research J Suarez Advances in Neural Information Processing Systems 34, 2021 | 6* | 2021 |
| Curious representation learning for embodied intelligence Y Du, C Gan, P Isola Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 6 | 2021 |
| Pre-trained language models for interactive decision-making S Li, X Puig, Y Du, C Wang, E Akyurek, A Torralba, J Andreas, I Mordatch arXiv preprint arXiv:2202.01771, 2022 | 5 | 2022 |
Igor MordatchUC BerkeleyEmail verificata su berkeley.edu
