publications

2024

  1. sedd.gif
    Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
    Aaron Lou, Chenlin Meng, and Stefano Ermon
    In International Conference on Machine Learning, 2024
    Best Paper Award
    arXiv Blog Code
  2. ICML
    Equivariant Graph Neural Operator for Modeling 3D Dynamics
    Minkai Xu, Jiaqi Han, Aaron Lou, Jean Kossaifi, Arvind Ramanathan, Kamyar Azizzadenesheli, Jure Leskovec, Stefano Ermon, and Anima Anandkumar
    In International Conference on Machine Learning, 2024
    arXiv Code
  3. diffusiondpo.jpg
    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, and Nikhil Naik
    In Conference on Computer Vision and Pattern Recognition, 2024
    arXiv Code
  4. ICLR
    Denoising Diffusion Bridge Models
    Linqi Zhou, Aaron Lou, Samar Khanna, and Stefano Ermon
    In International Conference on Learning Representations, 2024
    arXiv Code

2023

  1. NeurIPS
    Scaling Riemannian Diffusion Models
    Aaron Lou, Minkai Xu, and Stefano Ermon
    In Neural Information Processing Systems, 2023
    arXiv Code
  2. NeurIPS
    Riemannian Residual Neural Networks
    Isay Katsman, Eric Chen, Sidhanth Holalkere, Anna Asch, Aaron Lou, Ser-Nam Lim, and Christopher De Sa
    In Neural Information Processing Systems, 2023
    arXiv
  3. refldiff.gif
    Reflected Diffusion Models
    Aaron Lou, and Stefano Ermon
    In International Conference on Machine Learning, 2023
    arXiv Blog Code

2021

  1. neqmode.png
    Equivariant Manifold Flows
    Isay Katsman, Aaron Lou, Derek Lim, Qingxuan Jiang, Ser-Nam Lim, and Christopher De Sa
    In Neural Information Processing Systems, 2021
    arXiv Code
  2. NeurIPS
    Intrinsic Dimension, Persistent Homology and Generalization in Neural Networks
    Tolga Birdal, Aaron Lou, Leonidas J. Guibas, and Umut Simsekli
    In Neural Information Processing Systems, 2021
    arXiv Code

2020

  1. nmode.gif
    Neural Manifold Ordinary Differential Equations
    Aaron Lou, Derek Lim, Isay Katsman, Leo Huang, Qingxuan Jiang, Ser-Nam Lim, and Christopher De Sa
    In Neural Information Processing Systems, 2020
    arXiv Code
  2. frechet.png
    Differentiating through the Fréchet Mean
    Aaron Lou, Isay Katsman, Qingxuan Jiang, Serge Belongie, Ser-Nam Lim, and Christopher De Sa
    In International Conference on Machine Learning, 2020
    arXiv Code