Edmond Cunningham

PhD Candidate, UMass Amherst

prof_pic.jpg

I am completing my PhD at UMass Amherst this year and am actively seeking industry and post-doc positions. My research sits at the intersection of generative modeling and representation learning, where I am interested in characterizing the geometric structure of data in order to understand how to build better representations of data and interpretable generative models. Additionally, I have expertise in flow based and diffusion based generative models and have used them for image generation, time series modeling, variational inference, and Boltzmann sampling.

selected publications

  1. Preprint
    ar-fbgm.png
    On Autoregressive Time Series Generation using Flow-based Generative Models
    Edmond Cunningham, Madalina Fiterau, and Daniel Sheldon
    2025
  2. ICML
    principal-component-flows.png
    Principal Component Flows
    Edmond Cunningham, Adam D. Cobb, and Susmit Jha
    In Proceedings of the 39th International Conference on Machine Learning, 2022
    HTML
  3. AISTATS
    change-of-variables-rectangular.png
    A Change of Variables Method For Rectangular Matrix-Vector Products
    Edmond Cunningham and Madalina Fiterau
    In Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021
    HTML