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2020 – today
- 2024
[c6]Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff:
Statistical Spatially Inhomogeneous Diffusion Inference. AAAI 2024: 14820-14828- [i10]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) - [i9]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) - [i8]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) - [i7]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) - 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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