Skip to content

This page was last updated on 2025-11-10 06:13:04 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 4297 75
visibility_off Physics-informed learning of governing equations from scarce data Zhao Chen, Yang Liu, Hao Sun 2020-05-05 Nature Communications 476 14
visibility_off Deep learning of physical laws from scarce data Zhao Chen, Yang Liu, Hao Sun 2020-05-05 ArXiv 19 14
visibility_off Modeling of dynamical systems through deep learning P. Rajendra, V. Brahmajirao 2020-11-22 Biophysical Reviews 54 4
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 26 34
visibility_off Hierarchical Physics-Embedded Learning for Spatiotemporal Dynamical Systems Xizhe Wang, Xiaobin Song, Qingshan Jia, Hongbo Zhao, Benben Jiang 2025-10-29 ArXiv 0 3
visibility_off Symbolic regression via neural networks. N. Boddupalli, T. Matchen, J. Moehlis 2023-08-01 Chaos 12 37
visibility_off Automatically discovering ordinary differential equations from data with sparse regression Kevin Egan, Weizhen Li, Rui Carvalho 2024-01-09 Communications Physics 28 2
visibility_off Discovering sparse interpretable dynamics from partial observations Peter Y. Lu, Joan Ariño Bernad, M. Soljačić 2021-07-22 Communications Physics 33 97
visibility_off Sparse Estimation for Hamiltonian Mechanics Yuya Note, Masahito Watanabe, Hiroaki Yoshimura, Takaharu Yaguchi, Toshiaki Omori 2024-03-25 Mathematics 0 11
Abstract Title Authors Publication Date Journal/Conference Citation count Highest h-index