Henry Li

Yale University.

prof_pic.jpg

Arthur K Watson Hall Room 101

51 Prospect St

New Haven, CT 06511

I am a PhD student in the Applied Math Program at Yale University. I work with Yuval Kluger and Ronald Coifman on various topics in machine learning. I am particularly interested in principled approaches to likelihood-based generative modeling.

selected publications

  1. arXiv
    Fast and Noise-Robust Diffusion Solvers for Inverse Problems: A Frequentist Approach
    Li, Henry, Patsenker, Jonathan, Ko, Myeongseob, Jia, Ruoxi, and Kluger, Yuval
    In arXiv 2024
    PDF
  2. NeurIPS
    Boosting Alignment for Post-Unlearning Text-to-Image Generative Models
    Ko, Myeongseob,  Li, Henry, Wang, Zhun, Patsenker, Jonathan, Wang, Jiachen T., Li, Qinbin, Jin, Ming, Song, Dawn, and Jia, Ruoxi
    In NeurIPS 2024
    PDF
  3. NeurIPS
    Solving Inverse Problems via Diffusion Optimal Control
    Li, Henry, and Pereira, Marcus
    In NeurIPS 2024
    PDF
  4. ICLR (Spotlight)
    Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps
    Li, Henry, Basri, Ronen, and Kluger, Yuval
    In ICLR 2024
    HTML Poster
  5. NeurIPS
    Noise-conditional Maximum Likelihood Estimation with Score-based Sampling
    Li, Henry, and Kluger, Yuval
    In NeurIPS Workshop on Score-Based Methods 2022
    PDF
  6. ICML
    Neural Inverse Transform Sampler
    Li, Henry, and Kluger, Yuval
    In International Conference on Machine Learning 2022
    PDF Poster Slides