Data-driven discovery of free-form governing differential equations

27 September 2019

Liping Wang

Papers citing "Data-driven discovery of free-form governing differential equations"

22 / 22 papers shown

Title
A data-driven approach to modeling brain activity using differential equations Kuratov Andrey 28 0 0 14 Apr 2024
Towards stable real-world equation discovery with assessing differentiating quality influence Mikhail Masliaev Ilya Markov Alexander Hvatov 27 0 0 09 Nov 2023
ODEFormer: Symbolic Regression of Dynamical Systems with Transformers Stéphane d’Ascoli Soren Becker Alexander Mathis Philippe Schwaller Niki Kilbertus 29 22 0 09 Oct 2023
Weak-PDE-LEARN: A Weak Form Based Approach to Discovering PDEs From Noisy, Limited Data R. Stephany Christopher Earls 27 4 0 09 Sep 2023
Directed differential equation discovery using modified mutation and cross-over operators E. Ivanchik A. Hvatov 21 0 0 09 Aug 2023
Towards true discovery of the differential equations A. Hvatov Roman V. Titov 24 0 0 09 Aug 2023
Predicting Ordinary Differential Equations with Transformers Soren Becker M. Klein Alexander Neitz Giambattista Parascandolo Niki Kilbertus 35 15 0 24 Jul 2023
Interpretable Machine Learning for Science with PySR and SymbolicRegression.jl M. Cranmer 41 39 0 02 May 2023
Deep-OSG: Deep Learning of Operators in Semigroup Junfeng Chen Kailiang Wu AI4TS 17 6 0 07 Feb 2023
PDE-LEARN: Using Deep Learning to Discover Partial Differential Equations from Noisy, Limited Data R. Stephany Christopher Earls 16 16 0 09 Dec 2022
Discovering ordinary differential equations that govern time-series Soren Becker M. Klein Alexander Neitz Giambattista Parascandolo Niki Kilbertus AI4TS 27 4 0 05 Nov 2022
Rediscovering orbital mechanics with machine learning Pablo Lemos N. Jeffrey M. Cranmer S. Ho Peter W. Battaglia PINN AI4CE 19 86 0 04 Feb 2022
PDE-READ: Human-readable Partial Differential Equation Discovery using Deep Learning R. Stephany Christopher Earls DiffM AIMat 14 29 0 01 Nov 2021
Identifying Physical Law of Hamiltonian Systems via Meta-Learning Seungjun Lee Haesang Yang W. Seong 30 13 0 23 Feb 2021
Data-based Discovery of Governing Equations W. Subber Piyush Pandita Sayan Ghosh Genghis Khan Liping Wang R. Ghanem PINN AI4CE 12 1 0 05 Dec 2020
Deep-learning based discovery of partial differential equations in integral form from sparse and noisy data Hao Xu Dongxiao Zhang Nanzhe Wang 29 33 0 24 Nov 2020
Kernel-based parameter estimation of dynamical systems with unknown observation functions Ofir Lindenbaum A. Sagiv Gal Mishne Ronen Talmon 13 5 0 09 Sep 2020
Discovering Symbolic Models from Deep Learning with Inductive Biases M. Cranmer Alvaro Sanchez-Gonzalez Peter W. Battaglia Rui Xu Kyle Cranmer D. Spergel S. Ho AI4CE 19 465 0 19 Jun 2020
Bayesian Hidden Physics Models: Uncertainty Quantification for Discovery of Nonlinear Partial Differential Operators from Data Steven Atkinson 16 8 0 07 Jun 2020
Deep-learning of Parametric Partial Differential Equations from Sparse and Noisy Data Hao Xu Dongxiao Zhang Junsheng Zeng 25 57 0 16 May 2020
DLGA-PDE: Discovery of PDEs with incomplete candidate library via combination of deep learning and genetic algorithm Hao Xu Haibin Chang Dongxiao Zhang AI4CE 25 87 0 21 Jan 2020
Computational model discovery with reinforcement learning M. Bassenne A. Lozano-Durán 15 10 0 29 Dec 2019