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. ICLR (Spotlight)
    Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps
    Li, Henry, Basri, Ronen, and Kluger, Yuval
    In ICLR 2024
    PDF
  2. ICML
    Non-normal Diffusion Models
    Li, Henry
    In ICML Structured Probabilistic Inference & Generative Modeling 2023
    PDF Poster
  3. ICML
    Exponential weight averaging as damped harmonic motion
    Patsenker*, Jon, Li*, Henry, and Kluger, Yuval
    In ICML Frontiers in Learning, Control, and Dynamical Systems 2023
    PDF Poster
  4. NeurIPS
    Noise-conditional Maximum Likelihood Estimation with Score-based Sampling
    Li, Henry, and Kluger, Yuval
    In NeurIPS Workshop on Score-Based Methods 2022
    PDF
  5. ICML
    Neural Inverse Transform Sampler
    Li, Henry, and Kluger, Yuval
    In International Conference on Machine Learning 2022
    PDF Poster Slides
  6. ECCV
    Variational diffusion autoencoders with random walk sampling
    Li, Henry, Lindenbaum, Ofir, Cheng, Xiuyuan, and Cloninger, Alexander
    In European Conference on Computer Vision 2020
    PDF
  7. ICLR
    SpectralNet: Spectral Clustering using Deep Neural Networks
    Shaham, Uri, Stanton, Kelly,  Li, Henry, Basri, Ronen, Nadler, Boaz, and Kluger, Yuval
    In International Conference on Learning Representations 2018
    PDF