Aaron Lou

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 20

Top Topics

Diffusion Models

Differential Equations

Intrinsic Dimension

Top Venues

Publications

Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
Denoising Diffusion Bridge Models. ICLR (2024)
Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, Anima Anandkumar
Equivariant Graph Neural Operator for Modeling 3D Dynamics. CoRR (2024)
Aaron Lou, Minkai Xu, Stefano Ermon
Scaling Riemannian Diffusion Models. CoRR (2023)
Aaron Lou, Stefano Ermon
Reflected Diffusion Models. ICML (2023)
Linqi Zhou, Aaron Lou, Samar Khanna, Stefano Ermon
Denoising Diffusion Bridge Models. CoRR (2023)
Aaron Lou, Stefano Ermon
Reflected Diffusion Models. CoRR (2023)
Isay Katsman, Eric Ming Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser-Nam Lim, Christopher De Sa
Riemannian Residual Neural Networks. CoRR (2023)
Bram Wallace, Meihua Dang, Rafael Rafailov, Linqi Zhou, Aaron Lou, Senthil Purushwalkam, Stefano Ermon, Caiming Xiong, Shafiq Joty, Nikhil Naik
Diffusion Model Alignment Using Direct Preference Optimization. CoRR (2023)
Aaron Lou, Chenlin Meng, Stefano Ermon
Discrete Diffusion Language Modeling by Estimating the Ratios of the Data Distribution. CoRR (2023)
Isay Katsman, Eric Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser Nam Lim, Christopher De Sa
Riemannian Residual Neural Networks. NeurIPS (2023)
Aaron Lou, Minkai Xu, Adam Farris, Stefano Ermon
Scaling Riemannian Diffusion Models. NeurIPS (2023)
Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. CoRR (2021)
Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Equivariant Manifold Flows. CoRR (2021)
Tolga Birdal, Aaron Lou, Leonidas J. Guibas, Umut Simsekli
Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks. NeurIPS (2021)
Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Equivariant Manifold Flows. NeurIPS (2021)
Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Neural Manifold Ordinary Differential Equations. CoRR (2020)
Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa
Differentiating through the Fréchet Mean. ICML (2020)
Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, Christopher De Sa
Neural Manifold Ordinary Differential Equations. NeurIPS (2020)
Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge J. Belongie, Ser-Nam Lim, Christopher De Sa
Differentiating through the Fréchet Mean. CoRR (2020)
Horace He, Aaron Lou, Qingxuan Jiang, Isay Katsman, Pian Pawakapan, Serge J. Belongie, Ser-Nam Lim
Adversarial Example Decomposition. CoRR (2018)