| Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps C Lu, Y Zhou, F Bao, J Chen, C Li, J Zhu Advances in Neural Information Processing Systems 35, 5775-5787, 2022 | 892 | 2022 |
| Prolificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation Z Wang, C Lu, Y Wang, F Bao, C Li, H Su, J Zhu Advances in Neural Information Processing Systems 36, 2024 | 514 | 2024 |
| Dpm-solver++: Fast solver for guided sampling of diffusion probabilistic models C Lu, Y Zhou, F Bao, J Chen, C Li, J Zhu arXiv preprint arXiv:2211.01095, 2022 | 333 | 2022 |
| Analytic-dpm: an analytic estimate of the optimal reverse variance in diffusion probabilistic models F Bao, C Li, J Zhu, B Zhang arXiv preprint arXiv:2201.06503, 2022 | 297 | 2022 |
| All are worth words: A vit backbone for diffusion models F Bao, S Nie, K Xue, Y Cao, C Li, H Su, J Zhu Proceedings of the IEEE/CVF conference on computer vision and pattern
, 2023 | 230* | 2023 |
| Egsde: Unpaired image-to-image translation via energy-guided stochastic differential equations M Zhao, F Bao, C Li, J Zhu Advances in Neural Information Processing Systems 35, 3609-3623, 2022 | 169 | 2022 |
| One transformer fits all distributions in multi-modal diffusion at scale F Bao, S Nie, K Xue, C Li, S Pu, Y Wang, G Yue, Y Cao, H Su, J Zhu International Conference on Machine Learning, 1692-1717, 2023 | 108 | 2023 |
| Estimating the optimal covariance with imperfect mean in diffusion probabilistic models F Bao, C Li, J Sun, J Zhu, B Zhang arXiv preprint arXiv:2206.07309, 2022 | 71 | 2022 |
| Maximum likelihood training for score-based diffusion odes by high order denoising score matching C Lu, K Zheng, F Bao, J Chen, C Li, J Zhu International Conference on Machine Learning, 14429-14460, 2022 | 66 | 2022 |
| Equivariant energy-guided sde for inverse molecular design F Bao, M Zhao, Z Hao, P Li, C Li, J Zhu The eleventh international conference on learning representations, 2022 | 47 | 2022 |
| Revisiting discriminative vs. generative classifiers: Theory and implications C Zheng, G Wu, F Bao, Y Cao, C Li, J Zhu International Conference on Machine Learning, 42420-42477, 2023 | 31 | 2023 |
| Stability and generalization of bilevel programming in hyperparameter optimization F Bao, G Wu, C Li, J Zhu, B Zhang Advances in neural information processing systems 34, 4529-4541, 2021 | 28 | 2021 |
| Diffusion models and semi-supervised learners benefit mutually with few labels Z You, Y Zhong, F Bao, J Sun, C Li, J Zhu Advances in Neural Information Processing Systems 36, 2024 | 24 | 2024 |
| Vidu: a highly consistent, dynamic and skilled text-to-video generator with diffusion models F Bao, C Xiang, G Yue, G He, H Zhu, K Zheng, M Zhao, S Liu, Y Wang, ... arXiv preprint arXiv:2405.04233, 2024 | 17 | 2024 |
| Why are conditional generative models better than unconditional ones? F Bao, C Li, J Sun, J Zhu arXiv preprint arXiv:2212.00362, 2022 | 15 | 2022 |
| Bi-level score matching for learning energy-based latent variable models F Bao, C Li, K Xu, H Su, J Zhu, B Zhang Advances in Neural Information Processing Systems 33, 18110-18122, 2020 | 15 | 2020 |
| A closer look at parameter-efficient tuning in diffusion models C Xiang, F Bao, C Li, H Su, J Zhu arXiv preprint arXiv:2303.18181, 2023 | 12 | 2023 |
| Variational (gradient) estimate of the score function in energy-based latent variable models F Bao, K Xu, C Li, L Hong, J Zhu, B Zhang International Conference on Machine Learning, 651-661, 2021 | 10 | 2021 |
| Gaussian mixture solvers for diffusion models H Guo, C Lu, F Bao, T Pang, S Yan, C Du, C Li Advances in Neural Information Processing Systems 36, 2024 | 8 | 2024 |
| Diffusion Bridge Implicit Models K Zheng, G He, J Chen, F Bao, J Zhu arXiv preprint arXiv:2405.15885, 2024 | | 2024 |
