| Human mobility networks reveal increased segregation in large cities H Nilforoshan, W Looi, E Pierson, B Villanueva, N Fishman, Y Chen, ... Nature 624 (7992), 586-592, 2023 | 58 | 2023 |
| Diffusion models for constrained domains N Fishman, L Klarner, V De Bortoli, E Mathieu, M Hutchinson Transactions on Machine Learning Research, 2023 | 36 | 2023 |
| Change we can believe in: Structural and content dynamics within belief networks N Fishman, NT Davis American Journal of Political Science 66 (3), 648-663, 2022 | 32 | 2022 |
| Metropolis sampling for constrained diffusion models N Fishman, L Klarner, E Mathieu, M Hutchinson, V De Bortoli Advances in Neural Information Processing Systems 36, 2024 | 13 | 2024 |
| Should attention be all we need? The epistemic and ethical implications of unification in machine learning N Fishman, L Hancox-Li Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022 | 10 | 2022 |
| kundajelab/simdna: simulated datasets of DNA, June 2019 A Shrikumar, N Fishman, A Kundaje URL https://doi. org/10.5281/zenodo 3258813, 0 | 2 | |
| The Fragility of Fairness: Causal Sensitivity Analysis for Fair Machine Learning J Fawkes, N Fishman, M Andrews, ZC Lipton arXiv preprint arXiv:2410.09600, 2024 | | 2024 |
| Making (Global) Criminal Procedure: Empire, the End of Justice, and the Rise of Efficiency N Fishman Stanford University, 2021 | | 2021 |
| Fleeing from Terror: Considering Safety When Designing Public Spaces in the Age of Mass Murder N Fishman Pathways: Stanford Journal of Public Health (SJPH) 7, 2018 | | 2018 |
| Denoising ATAC-seq with Convolutional Neural N Fishman, S Gurev | | |
| Estimating Vote Choice in US Elections with Approximate Poisson-Binomial Logistic Regression N Fishman, E Rosenman OPT 2024: Optimization for Machine Learning, 0 | | |
| Understanding Transcriptional Regulatory Logic Using Convolutional and Generative Deep Learning Models N Fishman, GK Marinov, A Kundaje | | |
