Should attention be all we need? The epistemic and ethical implications of unification in machine learning. - Nic Fishman; Leif Hancox-Li (FAccT, 2022)

Human interaction networks reveal that large cities facilitate segregation. - Hamed Nilforoshan; Wenli Looi; Emma Pierson; Blanca Villanueva; Nic Fishman; Yiling Chen; John Sholar; Beth Redbird; David Grusky; Jure Leskovec (CoRR, 2022)

Metropolis Sampling for Constrained Diffusion Models. - Nic Fishman; Leo Klarner; Emile Mathieu; Michael J. Hutchinson; Valentin De Bortoli (NeurIPS, 2023)

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; Jure Leskovec (Nat., 2023)

Diffusion Models for Constrained Domains. - Nic Fishman; Leo Klarner; Valentin De Bortoli; Emile Mathieu; Michael John Hutchinson (Trans. Mach. Learn. Res., 2023)

The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning. - Jake Fawkes; Nic Fishman; Mel Andrews; Zachary C. Lipton (NeurIPS, 2024)

Generative Distribution Embeddings. - Nic Fishman; Gokul Gowri; Peng Yin; Jonathan Gootenberg; Omar Abudayyeh (CoRR, 2025)