| Universality of empirical risk minimization A Montanari, BN Saeed Conference on Learning Theory, 4310-4312, 2022 | 114 | 2022 |
| Ordering-based causal structure learning in the presence of latent variables D Bernstein, B Saeed, C Squires, C Uhler International conference on artificial intelligence and statistics, 4098-4108, 2020 | 58 | 2020 |
| Causal structure discovery from distributions arising from mixtures of dags B Saeed, S Panigrahi, C Uhler International Conference on Machine Learning, 8336-8345, 2020 | 38 | 2020 |
| Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints I Yildirim, T Gerstenberg, B Saeed, M Toussaint, J Tenenbaum arXiv preprint arXiv:1707.08212, 2017 | 19 | 2017 |
| Explaining intuitive difficulty judgments by modeling physical effort and risk I Yildirim, B Saeed, G Bennett-Pierre, T Gerstenberg, J Tenenbaum, ... arXiv preprint arXiv:1905.04445, 2019 | 16 | 2019 |
| Anchored causal inference in the presence of measurement error B Saeed, A Belyaeva, Y Wang, C Uhler Conference on uncertainty in artificial intelligence, 619-628, 2020 | 15 | 2020 |
| A non-asymptotic theory of Kernel Ridge Regression: deterministic equivalents, test error, and GCV estimator T Misiakiewicz, B Saeed arXiv preprint arXiv:2403.08938, 2024 | 10 | 2024 |
| Universality of max-margin classifiers A Montanari, F Ruan, B Saeed, Y Sohn arXiv preprint arXiv:2310.00176, 2023 | 5 | 2023 |
| Local minima of the empirical risk in high dimension: General theorems and convex examples K Asgari, A Montanari, B Saeed arXiv preprint arXiv:2502.01953, 2025 | | 2025 |
| Learning directed graphical models with latent variables B Saeed Massachusetts Institute of Technology, 2020 | | 2020 |
