| 2025 | ICLR | Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data. | Hengyu Fu, Zehao Dou, Jiawei Guo, Mengdi Wang, Minshuo Chen |
| 2025 | ICLR | On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality. | Jerry Yao-Chieh Hu, Weimin Wu, Yi-Chen Lee, Yu-Chao Huang, Minshuo Chen, Han Liu |
| 2024 | AISTATS | Policy Evaluation for Reinforcement Learning from Human Feedback: A Sample Complexity Analysis. | Zihao Li, Xiang Ji, Minshuo Chen, Mengdi Wang |
| 2024 | ICLR | Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight. | Jiacheng Guo, Minshuo Chen, Huan Wang, Caiming Xiong, Mengdi Wang, Yu Bai |
| 2024 | ICML | Theory of Consistency Diffusion Models: Distribution Estimation Meets Fast Sampling. | Zehao Dou, Minshuo Chen, Mengdi Wang, Zhuoran Yang |
| 2024 | ICML | Theoretical insights for diffusion guidance: A case study for Gaussian mixture models. | Yuchen Wu, Minshuo Chen, Zihao Li, Mengdi Wang, Yuting Wei |
| 2024 | KDD | Counterfactual Generative Models for Time-Varying Treatments. | Shenghao Wu, Wenbin Zhou, Minshuo Chen, Shixiang Zhu |
| 2023 | ICLR | Sample Complexity of Nonparametric Off-Policy Evaluation on Low-Dimensional Manifolds using Deep Networks. | Xiang Ji, Minshuo Chen, Mengdi Wang, Tuo Zhao |
| 2023 | ICLR | Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning. | Qingru Zhang, Minshuo Chen, Alexander Bukharin, Pengcheng He, Yu Cheng, Weizhu Chen, Tuo Zhao |
| 2023 | ICML | Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data. | Minshuo Chen, Kaixuan Huang, Tuo Zhao, Mengdi Wang |
| 2023 | ICML | Effective Minkowski Dimension of Deep Nonparametric Regression: Function Approximation and Statistical Theories. | Zixuan Zhang, Minshuo Chen, Mengdi Wang, Wenjing Liao, Tuo Zhao |
| 2023 | IECON | Design and Analysis of a Field Modulated Transverse Flux Linear Generator Used in Direct Drive Wave Energy Converter. | Minshuo Chen, Lei Huang, Yuan Li, Jiyu Zhang, Peiwen Tan, Ghulam Ahmad |
| 2022 | ICLR | Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect. | Yuqing Wang, Minshuo Chen, Tuo Zhao, Molei Tao |
| 2022 | ICML | Benefits of Overparameterized Convolutional Residual Networks: Function Approximation under Smoothness Constraint. | Hao Liu, Minshuo Chen, Siawpeng Er, Wenjing Liao, Tong Zhang, Tuo Zhao |
| 2022 | IECON | Optimal Energy Management Scheme for Wave-HESS DC Microgrid. | Peiwen Tan, Lei Huang, Minshuo Chen, Yang Li, Ruiyang Ma, Jianlong Yang |
| 2021 | ACL | Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization. | Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen |
| 2021 | ICML | How Important is the Train-Validation Split in Meta-Learning? | Yu Bai, Minshuo Chen, Pan Zhou, Tuo Zhao, Jason D. Lee, Sham M. Kakade, Huan Wang, Caiming Xiong |
| 2021 | ICML | Besov Function Approximation and Binary Classification on Low-Dimensional Manifolds Using Convolutional Residual Networks. | Hao Liu, Minshuo Chen, Tuo Zhao, Wenjing Liao |
| 2020 | AISTATS | On Generalization Bounds of a Family of Recurrent Neural Networks. | Minshuo Chen, Xingguo Li, Tuo Zhao |
| 2020 | ICLR | On Computation and Generalization of Generative Adversarial Imitation Learning. | Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao |
| 2019 | ICLR | On Computation and Generalization of Generative Adversarial Networks under Spectrum Control. | Haoming Jiang, Zhehui Chen, Minshuo Chen, Feng Liu, Dingding Wang, Tuo Zhao |
| 2019 | ICLR | On Scalable and Efficient Computation of Large Scale Optimal Transport. | Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha |
| 2019 | ICML | On Scalable and Efficient Computation of Large Scale Optimal Transport. | Yujia Xie, Minshuo Chen, Haoming Jiang, Tuo Zhao, Hongyuan Zha |