Symbolic regression
This page was last updated on 2025-03-03 06:06:34 UTC
Manually curated articles on Symbolic regression
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index | View recommendations |
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Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
View recommendations
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| visibility_off | Discovering governing equations from data by sparse identification of nonlinear dynamical systems | S. Brunton, J. Proctor, J. Kutz | 2015-09-11 | Proceedings of the National Academy of Sciences of the United States of America, Proceedings of the National Academy of Sciences | 3591 | 68 | open_in_new |
| visibility_off | Robust learning from noisy, incomplete, high-dimensional experimental data via physically constrained symbolic regression | Patrick A. K. Reinbold, Logan Kageorge, M. Schatz, R. Grigoriev | 2021-02-24 | Nature Communications | 97 | 24 | open_in_new |
| visibility_off | Data-driven discovery of coordinates and governing equations | Kathleen P. Champion, Bethany Lusch, J. Kutz, S. Brunton | 2019-03-29 | Proceedings of the National Academy of Sciences of the United States of America | 681 | 68 | open_in_new |
| visibility_off | Chaos as an intermittently forced linear system | S. Brunton, Bingni W. Brunton, J. Proctor, E. Kaiser, J. Kutz | 2016-08-18 | Nature Communications | 495 | 68 | open_in_new |
| visibility_off | Sparse identification of nonlinear dynamics for model predictive control in the low-data limit | E. Kaiser, J. Kutz, S. Brunton | 2017-11-15 | Proceedings. Mathematical, Physical, and Engineering Sciences, Proceedings of the Royal Society A | 488 | 68 | open_in_new |
| visibility_off | Inferring Biological Networks by Sparse Identification of Nonlinear Dynamics | N. Mangan, S. Brunton, J. Proctor, J. Kutz | 2016-05-26 | IEEE Transactions on Molecular, Biological and Multi-Scale Communications, IEEE Transactions on Molecular Biological and Multi-Scale Communications | 343 | 68 | open_in_new |
| visibility_off | SINDy-PI: a robust algorithm for parallel implicit sparse identification of nonlinear dynamics | Kadierdan Kaheman, J. Kutz, S. Brunton | 2020-04-05 | Proceedings. Mathematical, Physical, and Engineering Sciences, Proceedings of the Royal Society A | 238 | 68 | open_in_new |
| visibility_off | Multidimensional Approximation of Nonlinear Dynamical Systems | Patrick Gelß, Stefan Klus, J. Eisert, Christof Schutte | 2018-09-07 | Journal of Computational and Nonlinear Dynamics | 67 | 80 | open_in_new |
| visibility_off | Learning Discrepancy Models From Experimental Data | Kadierdan Kaheman, E. Kaiser, B. Strom, J. Kutz, S. Brunton | 2019-09-18 | arXiv.org, ArXiv | 38 | 68 | open_in_new |
| visibility_off | Discovery of Physics From Data: Universal Laws and Discrepancies | Brian M. de Silva, D. Higdon, S. Brunton, J. Kutz | 2019-06-19 | Frontiers in Artificial Intelligence | 79 | 68 | open_in_new |
Showing 1 to 10 of 14 entries
Recommended articles on Symbolic regression
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |
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| visibility_off | Impilict Runge-Kutta based sparse identification of governing equations in biologically motivated systems | Mehrdad Anvari, H. Marasi, Hossein Kheiri | 2025-02-27 | ArXiv | 0 | 2 |
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| visibility_off | Invariant Measures for Data-Driven Dynamical System Identification: Analysis and Application | Jonah Botvinick-Greenhouse | 2025-01-31 | ArXiv | 0 | 3 |
| visibility_off | Physics-Aware Sparse Signal Recovery Through PDE-Governed Measurement Systems | Tadashi Wadayama, Koji Igarashi, Takumi Takahashi | 2025-01-23 | ArXiv | 1 | 1 |
| visibility_off | Characterizing nonlinear dynamics by contrastive cartography | Nicolas Romeo, Chris Chi, Aaron R. Dinner, Elizabeth R. Jerison | 2025-01-30 | ArXiv | 0 | 3 |
| visibility_off | Data-driven system identification using quadratic embeddings of nonlinear dynamics | Stefan Klus, J. N'konzi | 2025-01-14 | ArXiv | 0 | 2 |
Showing 1 to 10 of 45 entries