| Invariant theory and scaling algorithms for maximum likelihood estimation C Améndola, K Kohn, P Reichenbach, A Seigal SIAM Journal on Applied Algebra and Geometry 5 (2), 304-337, 2021 | 51 | 2021 |
| Toric invariant theory for maximum likelihood estimation in log-linear models C Améndola, K Kohn, P Reichenbach, A Seigal Algebraic Statistics 12 (2), 187-211, 2021 | 12 | 2021 |
| Tensor rank and complexity G Ottaviani, P Reichenbach arXiv preprint arXiv:2004.01492, 2020 | 12 | 2020 |
| Symmetries in directed Gaussian graphical models V Makam, P Reichenbach, A Seigal Electronic Journal of Statistics 17 (2), 3969-4010, 2023 | 9 | 2023 |
| Barriers for recent methods in geodesic optimization C Franks, P Reichenbach arXiv preprint arXiv:2102.06652, 2021 | 9 | 2021 |
| Invariant theory in computational complexity and algebraic statistics P Reichenbach Dissertation, Berlin, Technische Universität Berlin, 2023, 2023 | 3 | 2023 |
| Complete collineations for maximum likelihood estimation G Bérczi, E Hamilton, P Reichenbach, A Seigal arXiv preprint arXiv:2311.03329, 2023 | 1 | 2023 |
| Corrigendum: Invariant theory and scaling algorithms for maximum likelihood estimation C Améndola, K Kohn, P Reichenbach, A Seigal SIAM Journal on Applied Algebra and Geometry 8 (2), 460-463, 2024 | | 2024 |
| A Bridge between Invariant Theory and Maximum Likelihood Estimation C Améndola, K Kohn, P Reichenbach, A Seigal SIAM Review 66 (4), 721-747, 2024 | | 2024 |
| Invariant theory for maximum likelihood estimation P Reichenbach, C Améndola, K Kohn, A Seigal 2021 Spring Western Virtual Sectional Meeting, 0 | | |
Anna SeigalAssistant Professor of Applied Mathematics, Harvard UniversityVerified email at seas.harvard.edu
