Nic Fishman

Causal Inference · Machine Learning · Multiscale Modeling

For an always up-to-date list of publications see my Google Scholar page.

Published Papers

  1. Count Bridges enable Modeling and Deconvolving Transcriptomic Data
    Nic Fishman, Gokul Gowri, Tanush Kumar, Jiaqi Lu, Valentin De Bortoli, Jonathan S. Gootenberg, and Omar Abudayyeh
    ICLR, 2026
  2. Generative Distribution Embeddings
    Nic Fishman, Gokul Gowri, Peng Yin, Jonathan Gootenberg, and Omar Abudayyeh
    Advances in Neural Information Processing Systems, 2025
  3. Partisan disparities in the funding of science in the United States
    Alexander C Furnas, Nic Fishman, Leah Rosenstiel, and Dashun Wang
    Science, 2025
  4. Estimating Vote Choice in US Elections with Approximate Poisson-Binomial Logistic Regression
    Nic Fishman and Evan Rosenman
    OPT 2024, 2024
  5. The fragility of fairness: Causal sensitivity analysis for fair machine learning
    Jake Fawkes, Nic Fishman, Mel Andrews, and Zachary Lipton
    Advances in Neural Information Processing Systems, 2024
  6. Human mobility networks reveal increased segregation in large cities
    Hamed Nilforoshan, Wenli Looi, Emma Pierson, Blanca Villanueva, Nic Fishman, Yiling Chen, John Sholar, Beth Redbird, David Grusky, and Jure Leskovec
    Nature, 2023
  7. Diffusion models for constrained domains
    Nic Fishman, Leo Klarner, Valentin De Bortoli, Emile Mathieu, and Michael Hutchinson
    Transactions on Machine Learning Research, 2023
  8. Metropolis sampling for constrained diffusion models
    Nic Fishman, Leo Klarner, Emile Mathieu, Michael Hutchinson, and Valentin De Bortoli
    Advances in Neural Information Processing Systems, 2023
  9. Change we can believe in: Structural and content dynamics within belief networks
    Nic Fishman and Nicholas T Davis
    American Journal of Political Science, 2022
  10. Should attention be all we need? The epistemic and ethical implications of unification in machine learning
    Nic Fishman and Leif Hancox-Li
    Proceedings of the 2022 ACM Conference on Fairness, Accountability, and Transparency, 2022
  11. Systematic characterization of generative models for de novo design of regulatory DNA
    Fishman, N., Shrikumar, A., Marinov, G., Kundaje, and A.
    (Spotlight) International Conference on Machine Learning, Computational Biology Workshop, 2020

Working Papers

  1. Rethinking Repeatability in Observational Social Science
    Jonathan Ben-Menachem, Ari Galper, and Nic Fishman
    SocArXiv, 2025
  2. Making (Global) Criminal Procedure: Empire, the End of Justice, and the Rise of Efficiency
    Nic Fishman
    Stanford University, 2021
  3. Principled Models for Analyzing Max-Diff Surveys
    Fishman and N.