Sinho Chewi - RankMe

71 papers A* 21A 2B 2Journal 45Unranked 1

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Algorithmic warm starts for Hamiltonian Monte Carlo. CoRR Matthew S. Zhang, Jason M. Altschuler, Sinho Chewi
2026	J	`jnl`	Blind denoising diffusion models and the blessings of dimensionality. CoRR Zahra Kadkhodaie, Aram-Alexandre Pooladian, Sinho Chewi, Eero P. Simoncelli
2026	J	`jnl`	High-accuracy log-concave sampling with stochastic queries. CoRR Fan Chen, Sinho Chewi, Constantinos Daskalakis, Alexander Rakhlin
2026	J	`jnl`	High-accuracy sampling for diffusion models and log-concave distributions. CoRR Fan Chen, Sinho Chewi, Constantinos Daskalakis, Alexander Rakhlin
2026	J	`jnl`	Rod Flow: A Continuous-Time Model for Gradient Descent at the Edge of Stability. CoRR Eric Regis, Sinho Chewi
2026	J	`jnl`	Shifted Composition II: Shift Harnack Inequalities and Curvature Upper Bounds. IEEE Trans. Inf. Theory Jason M. Altschuler, Sinho Chewi
2026	J	`jnl`	Variational inference via radial transport. CoRR Luca Ghafourpour, Sinho Chewi, Alessio Figalli, Aram-Alexandre Pooladian
2025	J	`jnl`	Analysis of Langevin Monte Carlo from Poincaré to Log-Sobolev. Found. Comput. Math. Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li, Ruoqi Shen, Matthew Shunshi Zhang
2025	J	`jnl`	DDPM Score Matching and Distribution Learning. CoRR Sinho Chewi, Alkis Kalavasis, Anay Mehrotra, Omar Montasser
2025	J	`jnl`	Gaussian mixture layers for neural networks. CoRR Sinho Chewi, Philippe Rigollet, Yuling Yan
2025	J	`jnl`	Gaussian mixture layers for neural networks. Trans. Mach. Learn. Res. Sinho Chewi, Philippe Rigollet, Yuling Yan
2025	J	`jnl`	Shifted Composition I: Harnack and Reverse Transport Inequalities. IEEE Trans. Inf. Theory Jason M. Altschuler, Sinho Chewi
2025	J	`jnl`	Shifted Composition IV: Underdamped Langevin and Numerical Discretizations with Partial Acceleration. CoRR Jason M. Altschuler, Sinho Chewi, Matthew S. Zhang
2025	J	`jnl`	Stability of the Kim-Milman flow map. CoRR Sinho Chewi, Aram-Alexandre Pooladian, Matthew S. Zhang
2025	J	`jnl`	Sublinear iterations can suffice even for DDPMs. CoRR Matthew S. Zhang, Stephen Huan, Jerry Huang, Nicholas M. Boffi, Sitan Chen, Sinho Chewi
2025	J	`jnl`	Theory and computation for structured variational inference. CoRR Shunan Sheng, Bohan Wu, Bennett Zhu, Sinho Chewi, Aram-Alexandre Pooladian
2024	A*	`conf`	Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space. COLT Yiheng Jiang, Sinho Chewi, Aram-Alexandre Pooladian
2024	A*	`conf`	Fast parallel sampling under isoperimetry. COLT Nima Anari, Sinho Chewi, Thuy-Duong Vuong
2024	J	`jnl`	Fast parallel sampling under isoperimetry. CoRR Nima Anari, Sinho Chewi, Thuy-Duong Vuong
2024	J	`jnl`	Faster High-accuracy Log-concave Sampling via Algorithmic Warm Starts. J. ACM Jason M. Altschuler, Sinho Chewi
2024	J	`jnl`	Query Lower Bounds for Log-concave Sampling. J. ACM Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan
2024	A*	`conf`	Sampling from the Mean-Field Stationary Distribution. COLT Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li
2024	J	`jnl`	Sampling from the Mean-Field Stationary Distribution. CoRR Yunbum Kook, Matthew Shunshi Zhang, Sinho Chewi, Murat A. Erdogdu, Mufan Bill Li
2024	J	`jnl`	Shifted Composition II: Shift Harnack Inequalities and Curvature Upper Bounds. CoRR Jason M. Altschuler, Sinho Chewi
2024	J	`jnl`	Shifted Composition III: Local Error Framework for KL Divergence. CoRR Jason M. Altschuler, Sinho Chewi
2023	J	`jnl`	Algorithms for mean-field variational inference via polyhedral optimization in the Wasserstein space. CoRR Yiheng Jiang, Sinho Chewi, Aram-Alexandre Pooladian
2023	A*	`conf`	Faster high-accuracy log-concave sampling via algorithmic warm starts. FOCS Jason M. Altschuler, Sinho Chewi
2023	J	`jnl`	Faster high-accuracy log-concave sampling via algorithmic warm starts. CoRR Jason M. Altschuler, Sinho Chewi
2023	B	`conf`	Fisher information lower bounds for sampling. ALT Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu
2023	A*	`conf`	Forward-Backward Gaussian Variational Inference via JKO in the Bures-Wasserstein Space. ICML Michael Ziyang Diao, Krishna Balasubramanian, Sinho Chewi, Adil Salim
2023	J	`jnl`	Forward-backward Gaussian variational inference via JKO in the Bures-Wasserstein Space. CoRR Michael Diao, Krishnakumar Balasubramanian, Sinho Chewi, Adil Salim
2023	A*	`conf`	Improved Discretization Analysis for Underdamped Langevin Monte Carlo. COLT Matthew Shunshi Zhang, Sinho Chewi, Mufan (Bill) Li, Krishna Balasubramanian, Murat A. Erdogdu
2023	A*	`conf`	Learning threshold neurons via edge of stability. NeurIPS Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang
2023	B	`conf`	On the complexity of finding stationary points of smooth functions in one dimension. ALT Sinho Chewi, Sébastien Bubeck, Adil Salim
2023	A*	`conf`	Query lower bounds for log-concave sampling. FOCS Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan
2023	J	`jnl`	Query lower bounds for log-concave sampling. CoRR Sinho Chewi, Jaume de Dios Pont, Jerry Li, Chen Lu, Shyam Narayanan
2023	A*	`conf`	Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. ICLR Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru Zhang
2023	J	`jnl`	Shifted Composition I: Harnack and Reverse Transport Inequalities. CoRR Jason M. Altschuler, Sinho Chewi
2023	A*	`conf`	The probability flow ODE is provably fast. NeurIPS Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim
2023	J	`jnl`	The probability flow ODE is provably fast. CoRR Sitan Chen, Sinho Chewi, Holden Lee, Yuanzhi Li, Jianfeng Lu, Adil Salim
2022	A*	`conf`	Analysis of Langevin Monte Carlo from Poincare to Log-Sobolev. COLT Sinho Chewi, Murat A. Erdogdu, Mufan (Bill) Li, Ruoqi Shen, Shunshi Zhang
2022	J	`jnl`	Fisher information lower bounds for sampling. CoRR Sinho Chewi, Patrik Gerber, Holden Lee, Chen Lu
2022	J	`jnl`	Gaussian discrepancy: A probabilistic relaxation of vector balancing. Discret. Appl. Math. Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner
2022	A*	`conf`	Improved analysis for a proximal algorithm for sampling. COLT Yongxin Chen, Sinho Chewi, Adil Salim, Andre Wibisono
2022	J	`jnl`	Learning threshold neurons via the "edge of stability". CoRR Kwangjun Ahn, Sébastien Bubeck, Sinho Chewi, Yin Tat Lee, Felipe Suarez, Yi Zhang
2022	A	`conf`	Rejection sampling from shape-constrained distributions in sublinear time. AISTATS Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
2022	J	`jnl`	Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions. CoRR Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru R. Zhang
2022	A*	`conf`	The query complexity of sampling from strongly log-concave distributions in one dimension. COLT Sinho Chewi, Patrik R. Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
2022	A*	`conf`	Towards a Theory of Non-Log-Concave Sampling: First-Order Stationarity Guarantees for Langevin Monte Carlo. COLT Krishna Balasubramanian, Sinho Chewi, Murat A. Erdogdu, Adil Salim, Shunshi Zhang
2022	A*	`conf`	Variational inference via Wasserstein gradient flows. NeurIPS Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
2022	J	`jnl`	Variational inference via Wasserstein gradient flows. CoRR Marc Lambert, Sinho Chewi, Francis R. Bach, Silvère Bonnabel, Philippe Rigollet
2021	A*	`conf`	Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent. NeurIPS Jason M. Altschuler, Sinho Chewi, Patrik Gerber, Austin J. Stromme
2021	J	`jnl`	Averaging on the Bures-Wasserstein manifold: dimension-free convergence of gradient descent. CoRR Jason M. Altschuler, Sinho Chewi, Patrik Gerber, Austin J. Stromme
2021	A*	`conf`	Efficient constrained sampling via the mirror-Langevin algorithm. NeurIPS Kwangjun Ahn, Sinho Chewi
2021	A	`conf`	Fast and Smooth Interpolation on Wasserstein Space. AISTATS Sinho Chewi, Julien Clancy, Thibaut Le Gouic, Philippe Rigollet, George Stepaniants, Austin J. Stromme
2021	J	`jnl`	Gaussian discrepancy: a probabilistic relaxation of vector balancing. CoRR Sinho Chewi, Patrik Gerber, Philippe Rigollet, Paxton Turner
2021	A*	`conf`	Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. COLT Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet
2021	J	`jnl`	Rejection sampling from shape-constrained distributions in sublinear time. CoRR Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
2021	J	`jnl`	The entropic barrier is n-self-concordant. CoRR Sinho Chewi
2021	J	`jnl`	The query complexity of sampling from strongly log-concave distributions in one dimension. CoRR Sinho Chewi, Patrik Gerber, Chen Lu, Thibaut Le Gouic, Philippe Rigollet
2020	J	`jnl`	Efficient constrained sampling via the mirror-Langevin algorithm. CoRR Kwangjun Ahn, Sinho Chewi
2020	A*	`conf`	Exponential ergodicity of mirror-Langevin diffusions. NeurIPS Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin J. Stromme
2020	J	`jnl`	Exponential ergodicity of mirror-Langevin diffusions. CoRR Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet, Austin J. Stromme
2020	A*	`conf`	Gradient descent algorithms for Bures-Wasserstein barycenters. COLT Sinho Chewi, Tyler Maunu, Philippe Rigollet, Austin J. Stromme
2020	J	`jnl`	Optimal dimension dependence of the Metropolis-Adjusted Langevin Algorithm. CoRR Sinho Chewi, Chen Lu, Kwangjun Ahn, Xiang Cheng, Thibaut Le Gouic, Philippe Rigollet
2020	A*	`conf`	SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence. NeurIPS Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet
2020	J	`jnl`	SVGD as a kernelized Wasserstein gradient flow of the chi-squared divergence. CoRR Sinho Chewi, Thibaut Le Gouic, Chen Lu, Tyler Maunu, Philippe Rigollet
2019	—	`conf`	Matching Observations to Distributions: Efficient Estimation via Sparsified Hungarian Algorithm. Allerton Sinho Chewi, Forest Yang, Avishek Ghosh, Abhay Parekh, Kannan Ramchandran
2018	J	`jnl`	A Combinatorial Proof of a Formula of Biane and Chapuy. Electron. J. Comb. Sinho Chewi, Venkat Anantharam
2018	J	`jnl`	Online Absolute Ranking with Partial Information: A Bipartite Graph Matching Approach. CoRR Sinho Chewi, Forest Yang, Avishek Ghosh, Abhay Parekh, Kannan Ramchandran
2017	J	`jnl`	A combinatorial proof of a formula of Biane and Chapuy. CoRR Sinho Chewi, Venkat Anantharam