Lou, Aaron

13 publications

ICLR 2024 Denoising Diffusion Bridge Models Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon

CVPR 2024 Diffusion Model Alignment Using Direct Preference Optimization Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik

ICML 2024 Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution Aaron Lou, Chenlin Meng, Stefano Ermon

ICML 2024 Equivariant Graph Neural Operator for Modeling 3D Dynamics Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar

NeurIPS 2024 Geometric Trajectory Diffusion Models Jiaqi Han, Minkai Xu, Aaron Lou, Haotian Ye, Stefano Ermon

ICML 2023 Reflected Diffusion Models Aaron Lou, Stefano Ermon

NeurIPS 2023 Riemannian Residual Neural Networks Isay Katsman, Eric Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher M De Sa

NeurIPS 2023 Scaling Riemannian Diffusion Models Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon

NeurIPS 2021 Equivariant Manifold Flows Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser Nam Lim, Christopher M De Sa

ICMLW 2021 Equivariant Manifold Flows Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa

NeurIPS 2021 Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks Tolga Birdal, Aaron Lou, Leonidas Guibas, Umut Simsekli

ICML 2020 Differentiating Through the Fréchet Mean Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, Christopher De Sa

NeurIPS 2020 Neural Manifold Ordinary Differential Equations Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser Nam Lim, Christopher M De Sa