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2020 – today
- 2025
[c9]Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff, Lexing Ying:
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework. ICLR 2025- [c8]Javan Tahir, Surya Ganguli, Grant M. Rotskoff:
Features are fate: a theory of transfer learning in high-dimensional regression. ICML 2025 - [i16]Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying:
Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms. CoRR abs/2502.00234 (2025) - [i15]Yinuo Ren, Grant M. Rotskoff, Lexing Ying:
A Unified Approach to Analysis and Design of Denoising Markov Models. CoRR abs/2504.01938 (2025) - [i14]Andrew Ferguson, Marisa Lafleur, Lars Ruthotto, Jesse Thaler, Yuan-Sen Ting, Pratyush Tiwary, Soledad Villar, E. Paulo Alves, Jeremy Avigad, Simon Billinge, Camille L. Bilodeau, Keith Brown, Emmanuel J. Candès, Arghya Chattopadhyay, Bingqing Cheng, Jonathan Clausen, Connor W. Coley, Andrew J. Connolly, Fred Daum, Sijia Dong
, Chrisy Xiyu Du, Cora Dvorkin, Cristiano Fanelli, Eric B. Ford, Luis Manuel Frutos, Nicolás García Trillos, Cecilia Garraffo, Robert Ghrist, Rafael Gómez-Bombarelli, Gianluca Guadagni, Sreelekha Guggilam, Sergei Gukov, Juan B. Gutiérrez, Salman Habib, Johannes Hachmann, Boris Hanin, Philip C. Harris, Murray Holland, Elizabeth Holm, Hsin-Yuan Huang, Shih-Chieh Hsu, Nick Jackson, Olexandr Isayev, Heng Ji, Aggelos K. Katsaggelos, Jeremy Kepner, Yannis G. Kevrekidis, Michelle P. Kuchera, J. Nathan Kutz, Branislava Lalic, Ann Lee, Matt LeBlanc, Josiah Lim, Rebecca Lindsey, Yongmin Liu, Peter Y. Lu, Sudhir Malik, Vuk Mandic, Vidya B. Manian, Emeka P. Mazi, Pankaj Mehta, Peter Melchior, Brice Ménard, Jennifer Ngadiuba, Stella Offner, Elsa Olivetti, Shyue Ping Ong, Christopher Rackauckas, Philippe Rigollet, Chad Risko, Philip Romero, Grant M. Rotskoff, Brett Savoie, Uros Seljak, David Shih, Gary Shiu, Dima Shlyakhtenko, Eva Silverstein, Taylor Sparks, Thomas Strohmer, Christopher Stubbs, Stephen Thomas, Suriyanarayanan Vaikuntanathan, René Vidal, Francisco Villaescusa-Navarro, Gregory Voth, Benjamin Wandelt, Rachel Ward, Melanie Weber, Risa Wechsler, Stephen Whitelam, Olaf Wiest, Mike Williams, Zhuoran Yang, Yaroslava G. Yingling, Bin Yu, Shuwen Yue, Ann Zabludoff, Huimin Zhao, Tong Zhang:
The Future of Artificial Intelligence and the Mathematical and Physical Sciences (AI+MPS). CoRR abs/2509.02661 (2025) - [i13]Yinuo Ren, Wenhao Gao, Lexing Ying, Grant M. Rotskoff, Jiequn Han:
DriftLite: Lightweight Drift Control for Inference-Time Scaling of Diffusion Models. CoRR abs/2509.21655 (2025) - 2024
- [c7]Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff:
Statistical Spatially Inhomogeneous Diffusion Inference. AAAI 2024: 14820-14828 - [c6]Haoxuan Chen, Yinuo Ren, Lexing Ying, Grant M. Rotskoff:
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity. NeurIPS 2024 - [i12]Shriram Chennakesavalu, Frank Hu, Sebastian Ibarraran, Grant M. Rotskoff:
Energy Rank Alignment: Using Preference Optimization to Search Chemical Space at Scale. CoRR abs/2405.12961 (2024) - [i11]Haoxuan Chen, Yinuo Ren, Lexing Ying, Grant M. Rotskoff:
Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity. CoRR abs/2405.15986 (2024) - [i10]Luke Causer, Grant M. Rotskoff, Juan P. Garrahan:
Discrete generative diffusion models without stochastic differential equations: a tensor network approach. CoRR abs/2407.11133 (2024) - [i9]Frank Hu, Michael S. Chen, Grant M. Rotskoff, Matthew W. Kanan, Thomas E. Markland:
Accurate and efficient structure elucidation from routine one-dimensional NMR spectra using multitask machine learning. CoRR abs/2408.08284 (2024) - [i8]Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff, Lexing Ying:
How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework. CoRR abs/2410.03601 (2024) - [i7]Javan Tahir, Surya Ganguli, Grant M. Rotskoff:
Features are fate: a theory of transfer learning in high-dimensional regression. CoRR abs/2410.08194 (2024) - 2023
- [i6]Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff:
Statistical Spatially Inhomogeneous Diffusion Inference. CoRR abs/2312.05793 (2023) - 2021
- [c5]Grant M. Rotskoff, Andrew R. Mitchell, Eric Vanden-Eijnden:
Active Importance Sampling for Variational Objectives Dominated by Rare Events: Consequences for Optimization and Generalization. MSML 2021: 757-780 - [i5]Marylou Gabrié, Grant M. Rotskoff, Eric Vanden-Eijnden:
Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods. CoRR abs/2107.08001 (2021) - 2020
- [c4]Zhengdao Chen, Grant M. Rotskoff, Joan Bruna, Eric Vanden-Eijnden:
A Dynamical Central Limit Theorem for Shallow Neural Networks. NeurIPS 2020 - [c3]Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna:
A mean-field analysis of two-player zero-sum games. NeurIPS 2020 - [i4]Carles Domingo-Enrich, Samy Jelassi, Arthur Mensch, Grant M. Rotskoff, Joan Bruna:
A mean-field analysis of two-player zero-sum games. CoRR abs/2002.06277 (2020) - [i3]Zhengdao Chen, Grant M. Rotskoff, Joan Bruna, Eric Vanden-Eijnden:
A Dynamical Central Limit Theorem for Shallow Neural Networks. CoRR abs/2008.09623 (2020)
2010 – 2019
- 2019
- [c2]Grant M. Rotskoff, Samy Jelassi, Joan Bruna, Eric Vanden-Eijnden:
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically. ICML 2019: 5508-5517 - [i2]Grant M. Rotskoff, Samy Jelassi, Joan Bruna, Eric Vanden-Eijnden:
Global convergence of neuron birth-death dynamics. CoRR abs/1902.01843 (2019) - 2018
- [c1]Grant M. Rotskoff, Eric Vanden-Eijnden:
Parameters as interacting particles: long time convergence and asymptotic error scaling of neural networks. NeurIPS 2018: 7146-7155 - [i1]Grant M. Rotskoff, Eric Vanden-Eijnden:
Neural Networks as Interacting Particle Systems: Asymptotic Convexity of the Loss Landscape and Universal Scaling of the Approximation Error. CoRR abs/1805.00915 (2018)
Coauthor Index
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