Physics-informed learning of governing equations from scarce data

5 May 2020

Yang Liu

Papers citing "Physics-informed learning of governing equations from scarce data"

32 / 32 papers shown

Title
PIED: Physics-Informed Experimental Design for Inverse Problems Apivich Hemachandra Gregory Kang Ruey Lau Szu Hui Ng Bryan Kian Hsiang Low PINN 92 0 0 10 Mar 2025
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis Yasamin Jalalian Juan Felipe Osorio Ramirez Alexander W. Hsu Bamdad Hosseini H. Owhadi 160 0 0 02 Mar 2025
Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks Mouad Elaarabi Domenico Borzacchiello Yves Le Guennec Philippe Le Bot Sebastien Comas-Cardona 134 1 0 20 Jan 2025
PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems Bocheng Zeng Qi Wang Ming Yan Yang Liu Ruizhi Chengze Yi Zhang Hongsheng Liu Zidong Wang Hao Sun AI4CE 188 4 0 02 Oct 2024
SetPINNs: Set-based Physics-informed Neural Networks Mayank Nagda Phil Ostheimer Thomas Specht Frank Rhein Fabian Jirasek Stephan Mandt Marius Kloft Sophie Fellenz PINN 3DPC 171 1 0 30 Sep 2024
Discovery and inversion of the viscoelastic wave equation in inhomogeneous media Su Chen Yi Ding Hiroe Miyake Xiaojun Li 77 0 0 27 Sep 2024
Monte Carlo Neural PDE Solver for Learning PDEs via Probabilistic Representation Rui Zhang Qi Meng Rongchan Zhu Yue Wang Wenlei Shi Shihua Zhang Zhi-Ming Ma Tie-Yan Liu DiffM AI4CE 129 6 0 10 Feb 2023
Integration of knowledge and data in machine learning Yuntian Chen Dongxiao Zhang PINN 63 32 0 15 Feb 2022
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 135 909 0 28 Jul 2020
SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics Kadierdan Kaheman J. Nathan Kutz Steven L. Brunton 55 268 0 05 Apr 2020
Neural Operator: Graph Kernel Network for Partial Differential Equations Zong-Yi Li Nikola B. Kovachki Kamyar Azizzadenesheli Burigede Liu K. Bhattacharya Andrew M. Stuart Anima Anandkumar 196 736 0 07 Mar 2020
Deep Learning for Symbolic Mathematics Guillaume Lample François Charton 3DGS 102 411 0 02 Dec 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 245 2,131 0 08 Oct 2019
AutoCompress: An Automatic DNN Structured Pruning Framework for Ultra-High Compression Rates Ning Liu Xiaolong Ma Zhiyuan Xu Yanzhi Wang Jian Tang Jieping Ye 67 185 0 06 Jul 2019
Machine learning in cardiovascular flows modeling: Predicting arterial blood pressure from non-invasive 4D flow MRI data using physics-informed neural networks Georgios Kissas Yibo Yang E. Hwuang W. Witschey John A. Detre P. Perdikaris AI4CE 121 373 0 13 May 2019
DeepMoD: Deep learning for Model Discovery in noisy data G. Both Subham Choudhury P. Sens R. Kusters 55 115 0 20 Apr 2019
Adversarial Uncertainty Quantification in Physics-Informed Neural Networks Yibo Yang P. Perdikaris AI4CE PINN 120 359 0 09 Nov 2018
Learning stable and predictive structures in kinetic systems: Benefits of a causal approach Niklas Pfister Stefan Bauer J. Peters CML 29 41 0 28 Oct 2018
Data-driven Discovery of Cyber-Physical Systems Ye Yuan Xiuchuan Tang W. Pan Xiuna Li Wei Zhou Hai-Tao Zhang Han Ding J. Gonçalves PINN AI4CE 39 173 0 01 Oct 2018
Numerical Aspects for Approximating Governing Equations Using Data Kailiang Wu D. Xiu 47 68 0 24 Sep 2018
Quantifying total uncertainty in physics-informed neural networks for solving forward and inverse stochastic problems Dongkun Zhang Lu Lu Ling Guo George Karniadakis UQCV 105 408 0 21 Sep 2018
Data-driven discovery of PDEs in complex datasets Jens Berg K. Nystrom AI4CE PINN 51 141 0 31 Aug 2018
Deep Learning of Vortex Induced Vibrations M. Raissi Zhicheng Wang M. Triantafyllou George Karniadakis AI4CE 60 376 0 26 Aug 2018
Learning Equations for Extrapolation and Control Subham S. Sahoo Christoph H. Lampert Georg Martius 46 233 0 19 Jun 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations M. Raissi PINN AI4CE 118 754 0 20 Jan 2018
Deep learning for universal linear embeddings of nonlinear dynamics Bethany Lusch J. Nathan Kutz Steven L. Brunton 76 1,252 0 27 Dec 2017
Sparse learning of stochastic dynamic equations L. Boninsegna Feliks Nuske C. Clementi 40 217 0 06 Dec 2017
DGM: A deep learning algorithm for solving partial differential equations Justin A. Sirignano K. Spiliopoulos AI4CE 91 2,062 0 24 Aug 2017
Learning Structured Sparsity in Deep Neural Networks W. Wen Chunpeng Wu Yandan Wang Yiran Chen Hai Helen Li 178 2,339 0 12 Aug 2016
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 563 7,992 0 13 Jun 2015
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 160 2,808 0 20 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,115 0 22 Dec 2014