| 2026 | COLT | How Does the ReLU Activation Affect the Implicit Bias of Gradient Descent on High-dimensional Neural Network Regression? | Kuo-Wei Lai, Guanghui Wang, Molei Tao, Vidya Muthukumar |
| 2025 | AISTATS | Variational Schrdinger Momentum Diffusion. | Kevin Rojas, Yixin Tan, Molei Tao, Yuriy Nevmyvaka, Wei Deng |
| 2025 | ICLR | Provable Benefit of Annealed Langevin Monte Carlo for Non-log-concave Sampling. | Wei Guo, Molei Tao, Yongxin Chen |
| 2025 | ICLR | Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups. | Yuchen Zhu, Tianrong Chen, Lingkai Kong, Evangelos A. Theodorou, Molei Tao |
| 2025 | ICLR | Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images. | Sichen Zhu, Yuchen Zhu, Molei Tao, Peng Qiu |
| 2025 | ICML | Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces. | Kevin Rojas, Yuchen Zhu, Sichen Zhu, Felix X.-F. Ye, Molei Tao |
| 2025 | WACV | SODA: Spectral Orthogonal Decomposition Adaptation for Diffusion Models. | Xinxi Zhang, Song Wen, Ligong Han, Felix Juefei-Xu, Akash Srivastava, Junzhou Huang, Vladimir Pavlovic, Hao Wang, Molei Tao, Dimitris N. Metaxas |
| 2024 | AISTATS | Extragradient Type Methods for Riemannian Variational Inequality Problems. | Zihao Hu, Guanghui Wang, Xi Wang, Andre Wibisono, Jacob D. Abernethy, Molei Tao |
| 2024 | COLT | Convergence of Kinetic Langevin Monte Carlo on Lie groups. | Lingkai Kong, Molei Tao |
| 2023 | ICLR | Momentum Stiefel Optimizer, with Applications to Suitably-Orthogonal Attention, and Optimal Transport. | Lingkai Kong, Yuqing Wang, Molei Tao |
| 2023 | ICLR | gDDIM: Generalized denoising diffusion implicit models. | Qinsheng Zhang, Molei Tao, Yongxin Chen |
| 2022 | ALT | The Mirror Langevin Algorithm Converges with Vanishing Bias. | Ruilin Li, Molei Tao, Santosh S. Vempala, Andre Wibisono |
| 2022 | ICLR | Sqrt(d) Dimension Dependence of Langevin Monte Carlo. | Ruilin Li, Hongyuan Zha, Molei Tao |
| 2022 | ICLR | Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. | Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao |
| 2022 | ICML | Hessian-Free High-Resolution Nesterov Acceleration For Sampling. | Ruilin Li, Hongyuan Zha, Molei Tao |
| 2021 | ICML | Data-driven Prediction of General Hamiltonian Dynamics via Learning Exactly-Symplectic Maps. | Renyi Chen, Molei Tao |
| 2020 | AISTATS | Variational Optimization on Lie Groups, with Examples of Leading (Generalized) Eigenvalue Problems. | Molei Tao, Tomoki Ohsawa |