This page was last updated on 2025-01-13 06:05:53 UTC
Recommendations for the article Data-driven discovery of coordinates and governing equations
Abstract | Title | Authors | Publication Date | Journal/ Conference | Citation count | Highest h-index |
---|---|---|---|---|---|---|
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 | 3502 | 68 |
visibility_off | Physics-informed learning of governing equations from scarce data | Zhao Chen, Yang Liu, Hao Sun | 2020-05-05 | Nature Communications | 309 | 13 |
visibility_off | Deep learning of physical laws from scarce data | Zhao Chen, Yang Liu, Hao Sun | 2020-05-05 | ArXiv | 19 | 13 |
visibility_off | Modeling of dynamical systems through deep learning | P. Rajendra, V. Brahmajirao | 2020-11-22 | Biophysical Reviews | 39 | 5 |
visibility_off | Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants | Liyao (Mars) Gao, J. Kutz | 2022-11-19 | Proceedings of the Royal Society A | 13 | 33 |
visibility_off | Symbolic regression via neural networks. | N. Boddupalli, T. Matchen, J. Moehlis | 2023-08-01 | Chaos | 6 | 37 |
visibility_off | Automatically discovering ordinary differential equations from data with sparse regression | Kevin Egan, Weizhen Li, Rui Carvalho | 2024-01-09 | Communications Physics | 12 | 2 |
visibility_off | Discovering sparse interpretable dynamics from partial observations | Peter Y. Lu, Joan Ariño Bernad, M. Soljačić | 2021-07-22 | Communications Physics | 20 | 95 |
visibility_off | Sparse Estimation for Hamiltonian Mechanics | Yuya Note, Masahito Watanabe, Hiroaki Yoshimura, Takaharu Yaguchi, Toshiaki Omori | 2024-03-25 | Mathematics | 0 | 11 |
visibility_off | Uncovering Closed-form Governing Equations of Nonlinear Dynamics from Videos | Lele Luan, Yang Liu, Hao Sun | 2021-06-09 | ArXiv | 0 | 13 |
Abstract | Title | Authors | Publication Date | Journal/Conference | Citation count | Highest h-index |