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"

36 / 36 papers shown

Title
Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting Yingtao Luo Shikai Fang Binqing Wu Qingsong Wen Liang Sun BDL AI4CE 14 0 0 20 May 2025
Physics-informed Temporal Alignment for Auto-regressive PDE Foundation Models Congcong Zhu Xiaoyan Xu Jiayue Han Jingrun Chen OOD AI4CE 45 0 0 16 May 2025
PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Spatiotemporal Prediction Han Wan Qi Wang Hao Sun Hao Sun AI4CE 62 1 0 13 Mar 2025
PIED: Physics-Informed Experimental Design for Inverse Problems Apivich Hemachandra Gregory Kang Ruey Lau Szu Hui Ng Bryan Kian Hsiang Low PINN 50 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 48 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 88 1 0 20 Jan 2025
PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems Bocheng Zeng Qi Wang Ming Yan Yong-Jin Liu Ruizhi Chengze Yi Zhang Hongsheng Liu Zidong Wang Hao Sun AI4CE 47 3 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 3DPC PINN 49 1 0 30 Sep 2024
Discovery and inversion of the viscoelastic wave equation in inhomogeneous media Su Chen Yi Ding Hiroe Miyake Xiaojun Li 43 0 0 27 Sep 2024
Automating the Discovery of Partial Differential Equations in Dynamical Systems Weizhen Li Rui Carvalho 31 1 0 25 Apr 2024
Data-Driven Discovery of PDEs via the Adjoint Method Mohsen Sadr Tony Tohme Kamal Youcef-Toumi PINN 32 1 0 30 Jan 2024
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems Biao Yuan Ana Heitor He Wang Xiaohui Chen AI4CE PINN 37 1 0 08 Jan 2024
Deciphering and integrating invariants for neural operator learning with various physical mechanisms Rui Zhang Qi Meng Zhi-Ming Ma AI4CE 35 7 0 24 Nov 2023
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 37 10 0 08 Oct 2023
NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training B.-L. Lu Christian Moya Guang Lin PINN 37 11 0 03 Mar 2023
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 56 4 0 10 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
Physics-informed Neural Networks with Unknown Measurement Noise Philipp Pilar Niklas Wahlström PINN 25 6 0 28 Nov 2022
Robustness of Physics-Informed Neural Networks to Noise in Sensor Data Jian Cheng Wong P. Chiu C. Ooi My Ha Da 35 3 0 22 Nov 2022
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain Pu Ren Chengping Rao Su Chen Jian-Xun Wang Hao Sun Yang Liu 46 41 0 25 Oct 2022
DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learning Mengge Du Yuntian Chen Dong-juan Zhang 35 0 0 04 Oct 2022
Weak Collocation Regression method: fast reveal hidden stochastic dynamics from high-dimensional aggregate data Liwei Lu Zhijun Zeng Yan Jiang Yi Zhu Pipi Hu 33 4 0 06 Sep 2022
Noise-aware Physics-informed Machine Learning for Robust PDE Discovery Pongpisit Thanasutives Takeshi Morita M. Numao Ken-ichi Fukui PINN AI4CE 41 18 0 26 Jun 2022
CoNSoLe: Convex Neural Symbolic Learning Haoran Li Yang Weng Hanghang Tong 31 9 0 01 Jun 2022
A Priori Denoising Strategies for Sparse Identification of Nonlinear Dynamical Systems: A Comparative Study A. Cortiella K. Park Alireza Doostan 24 15 0 29 Jan 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning Chengping Rao Pu Ren Yang Liu Hao Sun AI4CE 45 28 0 28 Jan 2022
A generic physics-informed neural network-based framework for reliability assessment of multi-state systems Taotao Zhou Xiaoge Zhang E. Droguett A. Mosleh AI4CE 36 31 0 01 Dec 2021
Discovery of interpretable structural model errors by combining Bayesian sparse regression and data assimilation: A chaotic Kuramoto-Sivashinsky test case R. Mojgani Ashesh Chattopadhyay Pedram Hassanzadeh 29 15 0 01 Oct 2021
Variational Physics Informed Neural Networks: the role of quadratures and test functions S. Berrone C. Canuto Moreno Pintore 36 41 0 05 Sep 2021
Physics-informed Dyna-Style Model-Based Deep Reinforcement Learning for Dynamic Control Xin-Yang Liu Jian-Xun Wang AI4CE 31 38 0 31 Jul 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 48 211 0 16 Jul 2021
Physics-Guided Deep Learning for Dynamical Systems: A Survey Rui Wang Rose Yu AI4CE PINN 46 65 0 02 Jul 2021
PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs Pu Ren Chengping Rao Yang Liu Jianxun Wang Hao Sun DiffM AI4CE 51 193 0 26 Jun 2021
Physics-informed Spline Learning for Nonlinear Dynamics Discovery Fangzheng Sun Yang Liu Hao Sun AI4CE 20 28 0 05 May 2021
Revealing hidden dynamics from time-series data by ODENet Pipi Hu Wuyue Yang Yi Zhu L. Hong AI4TS 24 35 0 11 May 2020
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting Xingjian Shi Zhourong Chen Hao Wang Dit-Yan Yeung W. Wong W. Woo 239 7,921 0 13 Jun 2015