Rotskoff, Grant M.

10 publications

ICLRW 2025 Aligning Chemical and Protein Language Models with Continuous Feedback Using Energy Rank Alignment Shriram Chennakesavalu, Frank Hu, Sebastian Ibarraran, Grant M. Rotskoff

NeurIPS 2025 Aligning Transformers with Continuous Feedback via Energy Rank Alignment Shriram Chennakesavalu, Frank Hu, Sebastian Ibarraran, Grant M. Rotskoff

NeurIPS 2025 Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying

ICLRW 2025 Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms Yinuo Ren, Haoxuan Chen, Yuchen Zhu, Wei Guo, Yongxin Chen, Grant M. Rotskoff, Molei Tao, Lexing Ying

ICML 2025 Features Are Fate: A Theory of Transfer Learning in High-Dimensional Regression Javan Tahir, Surya Ganguli, Grant M. Rotskoff

ICLR 2025 How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff, Lexing Ying

NeurIPS 2024 Accelerating Diffusion Models with Parallel Sampling: Inference at Sub-Linear Time Complexity Haoxuan Chen, Yinuo Ren, Lexing Ying, Grant M. Rotskoff

NeurIPSW 2024 How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework Yinuo Ren, Haoxuan Chen, Grant M. Rotskoff, Lexing Ying

AAAI 2024 Statistical Spatially Inhomogeneous Diffusion Inference Yinuo Ren, Yiping Lu, Lexing Ying, Grant M. Rotskoff

ICMLW 2021 Efficient Bayesian Sampling Using Normalizing Flows to Assist Markov Chain Monte Carlo Methods Marylou Gabrié, Grant M. Rotskoff, Eric Vanden-Eijnden