| 2026 | COLT | High-Accuracy Log-Concave Sampling with Stochastic Queries. | Fan Chen, Sinho Chewi, Constantinos Daskalakis, Alexander Rakhlin |
| 2026 | COLT | DDPM Score Matching and Distribution Learning (Extended Abstract). | Sinho Chewi, Alkis Kalavasis, Anay Mehrotra, Omar Montasser |
| 2026 | STOC | Shifted Composition IV: Toward Ballistic Acceleration for Log-Concave Sampling. | Jason M. Altschuler, Sinho Chewi, Matthew S. Zhang |
| 2024 | COLT | Fast parallel sampling under isoperimetry. | Nima Anari, Sinho Chewi, Thuy-Duong Vuong |
| 2024 | COLT | Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space. | Yiheng Jiang, Sinho Chewi, Aram-Alexandre Pooladian |
| 2024 | COLT | Sampling from the Mean-Field Stationary Distribution. | Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li |
| 2023 | ALT | On the complexity of finding stationary points of smooth functions in one dimension. | Sinho Chewi, Sbastien Bubeck, Adil Salim |
| 2023 | ALT | Fisher information lower bounds for sampling. | Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu |
| 2023 | COLT | Improved Discretization Analysis for Underdamped Langevin Monte Carlo. | Matthew Shunshi Zhang, Sinho Chewi, Mufan (Bill) Li, Krishna Balasubramanian, Murat A. Erdogdu |
| 2023 | FOCS | Faster high-accuracy log-concave sampling via algorithmic warm starts. | Jason M. Altschuler, Sinho Chewi |
| 2023 | FOCS | Query lower bounds for log-concave sampling. | Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan |
| 2023 | ICLR | Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. | Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru Zhang |
| 2023 | ICML | Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space. | Michael Ziyang Diao, Krishna Balasubramanian, Sinho Chewi, Adil Salim |
| 2022 | AISTATS | Rejection sampling from shape-constrained distributions in sublinear time. | Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet |
| 2022 | COLT | Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo. | Krishna Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Shunshi Zhang |
| 2022 | COLT | Improved analysis for a proximal algorithm for sampling. | Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono |
| 2022 | COLT | Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev. | Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li, Ruoqi Shen, Shunshi Zhang |
| 2022 | COLT | The query complexity of sampling from strongly log-concave distributions in one dimension. | Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet |
| 2021 | AISTATS | Fast and Smooth Interpolation on Wasserstein Space. | Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin J. Stromme |
| 2021 | COLT | Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. | Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet |
| 2020 | COLT | Gradient descent algorithms for Bures-Wasserstein barycenters. | Sinho Chewi, Tyler Maunu, Philippe Rigollet, Austin J. Stromme |