| Denoising diffusion probabilistic models J Ho, A Jain, P Abbeel Advances in neural information processing systems 33, 6840-6851, 2020 | 3795 | 2020 |
| Generative adversarial imitation learning J Ho, S Ermon Advances in Neural Information Processing Systems, 4565-4573, 2016 | 2747 | 2016 |
| Evolution strategies as a scalable alternative to reinforcement learning T Salimans, J Ho, X Chen, S Sidor, I Sutskever arXiv preprint arXiv:1703.03864, 2017 | 1501 | 2017 |
| Photorealistic text-to-image diffusion models with deep language understanding C Saharia, W Chan, S Saxena, L Li, J Whang, EL Denton, K Ghasemipour, ... Advances in Neural Information Processing Systems 35, 36479-36494, 2022 | 1497 | 2022 |
| Classifier-free diffusion guidance J Ho, T Salimans arXiv preprint arXiv:2207.12598, 2022 | 730 | 2022 |
| Motion planning with sequential convex optimization and convex collision checking J Schulman, Y Duan, J Ho, A Lee, I Awwal, H Bradlow, J Pan, S Patil, ... The International Journal of Robotics Research 33 (9), 1251-1270, 2014 | 729 | 2014 |
| One-shot imitation learning Y Duan, M Andrychowicz, B Stadie, J Ho, J Schneider, I Sutskever, ... Advances in Neural Information Processing Systems, 1087-1098, 2017 | 694 | 2017 |
| Finding locally optimal, collision-free trajectories with sequential convex optimization. J Schulman, J Ho, AX Lee, I Awwal, H Bradlow, P Abbeel Robotics: science and systems 9 (1), 1-10, 2013 | 550 | 2013 |
| Image super-resolution via iterative refinement C Saharia, J Ho, W Chan, T Salimans, DJ Fleet, M Norouzi IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (4), 4713-4726, 2022 | 541 | 2022 |
| Palette: Image-to-image diffusion models C Saharia, W Chan, H Chang, C Lee, J Ho, T Salimans, D Fleet, ... ACM SIGGRAPH 2022 Conference Proceedings, 1-10, 2022 | 452 | 2022 |
| Cascaded Diffusion Models for High Fidelity Image Generation J Ho, C Saharia, W Chan, DJ Fleet, M Norouzi, T Salimans arXiv preprint arXiv:2106.15282, 2021 | 408 | 2021 |
| Flow++: Improving flow-based generative models with variational dequantization and architecture design J Ho, X Chen, A Srinivas, Y Duan, P Abbeel International Conference on Machine Learning, 2019 | 390 | 2019 |
| Variational diffusion models D Kingma, T Salimans, B Poole, J Ho Advances in neural information processing systems 34, 21696-21707, 2021 | 377 | 2021 |
| Axial attention in multidimensional transformers J Ho, N Kalchbrenner, D Weissenborn, T Salimans arXiv preprint arXiv:1912.12180, 2019 | 375 | 2019 |
| Meta learning shared hierarchies K Frans, J Ho, X Chen, P Abbeel, J Schulman arXiv preprint arXiv:1710.09767, 2017 | 375 | 2017 |
| Imagen video: High definition video generation with diffusion models J Ho, W Chan, C Saharia, J Whang, R Gao, A Gritsenko, DP Kingma, ... arXiv preprint arXiv:2210.02303, 2022 | 262 | 2022 |
| Progressive distillation for fast sampling of diffusion models T Salimans, J Ho arXiv preprint arXiv:2202.00512, 2022 | 260 | 2022 |
| Structured denoising diffusion models in discrete state-spaces J Austin, DD Johnson, J Ho, D Tarlow, R Van Den Berg Advances in Neural Information Processing Systems 34, 17981-17993, 2021 | 258 | 2021 |
| Evolved policy gradients R Houthooft, Y Chen, P Isola, B Stadie, F Wolski, J Ho, P Abbeel Advances in Neural Information Processing Systems, 5405-5414, 2018 | 245 | 2018 |
| Tracking deformable objects with point clouds J Schulman, A Lee, J Ho, P Abbeel 2013 IEEE International Conference on Robotics and Automation, 1130-1137, 2013 | 199 | 2013 |
