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DeepXDE: A deep learning library for solving differential equations

10 July 2019

Papers citing "DeepXDE: A deep learning library for solving differential equations"

34 / 484 papers shown

Title
Physics Informed Neural Networks for Simulating Radiative Transfer Siddhartha Mishra Roberto Molinaro PINN 91 110 0 25 Sep 2020
A fast and accurate physics-informed neural network reduced order model with shallow masked autoencoder Youngkyu Kim Youngsoo Choi David Widemann T. Zohdi AI4CE 74 200 0 25 Sep 2020
Discovery of Governing Equations with Recursive Deep Neural Networks Jia Zhao Jarrod Mau PINN 70 7 0 24 Sep 2020
Automatic Differentiation to Simultaneously Identify Nonlinear Dynamics and Extract Noise Probability Distributions from Data Kadierdan Kaheman Steven L. Brunton J. Nathan Kutz 85 84 0 12 Sep 2020
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism L. McClenny U. Braga-Neto PINN 98 465 0 07 Sep 2020
Uncertainty Quantification of Locally Nonlinear Dynamical Systems using Neural Networks Subhayan De 58 9 0 11 Aug 2020
When and why PINNs fail to train: A neural tangent kernel perspective Sizhuang He Xinling Yu P. Perdikaris 143 932 0 28 Jul 2020
Differentiable model-based adaptive optics with transmitted and reflected light Ivan Vishniakou Johannes D. Seelig MedIm 23 3 0 27 Jul 2020
An unsupervised learning approach to solving heat equations on chip based on Auto Encoder and Image Gradient Haiyang He Jay Pathak 74 24 0 19 Jul 2020
Expressivity of Deep Neural Networks Ingo Gühring Mones Raslan Gitta Kutyniok 97 51 0 09 Jul 2020
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks Colby Wight Jia Zhao 82 225 0 09 Jul 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating a class of inverse problems for PDEs Siddhartha Mishra Roberto Molinaro PINN 109 267 0 29 Jun 2020
Estimates on the generalization error of Physics Informed Neural Networks (PINNs) for approximating PDEs Siddhartha Mishra Roberto Molinaro PINN 79 173 0 29 Jun 2020
Deeply Learned Spectral Total Variation Decomposition T. G. Grossmann Yury Korolev Guy Gilboa Carola-Bibiane Schönlieb 67 4 0 17 Jun 2020
Solving Differential Equations Using Neural Network Solution Bundles Cedric Wen Flamant P. Protopapas David Sondak 59 29 0 17 Jun 2020
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization Rishikesh Ranade C. Hill Jay Pathak AI4CE 152 127 0 17 May 2020
A Combined Data-driven and Physics-driven Method for Steady Heat Conduction Prediction using Deep Convolutional Neural Networks Hao Ma Xiangyu Y. Hu Yuxuan Zhang Nils Thuerey O. Haidn AI4CE 48 12 0 16 May 2020
Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks Moritz Geist P. Petersen Mones Raslan R. Schneider Gitta Kutyniok 102 83 0 25 Apr 2020
Constrained Neural Ordinary Differential Equations with Stability Guarantees Aaron Tuor Ján Drgoňa D. Vrabie 76 25 0 22 Apr 2020
Accelerating Physics-Informed Neural Network Training with Prior Dictionaries Wei Peng Weien Zhou Jun Zhang Wen Yao PINN AI4CE 136 31 0 17 Apr 2020
SINDy-PI: A Robust Algorithm for Parallel Implicit Sparse Identification of Nonlinear Dynamics Kadierdan Kaheman J. Nathan Kutz Steven L. Brunton 76 275 0 05 Apr 2020
On the convergence of physics informed neural networks for linear second-order elliptic and parabolic type PDEs Yeonjong Shin Jérome Darbon George Karniadakis PINN 73 79 0 03 Apr 2020
B-PINNs: Bayesian Physics-Informed Neural Networks for Forward and Inverse PDE Problems with Noisy Data Liu Yang Xuhui Meng George Karniadakis PINN 247 797 0 13 Mar 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 216 544 0 11 Mar 2020
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 196 49 0 27 Feb 2020
Autonomous Discovery of Unknown Reaction Pathways from Data by Chemical Reaction Neural Network Weiqi Ji Sili Deng 44 108 0 20 Feb 2020
Universal Differential Equations for Scientific Machine Learning Christopher Rackauckas Yingbo Ma Julius Martensen Collin Warner K. Zubov R. Supekar Dominic J. Skinner Ali Ramadhan Alan Edelman AI4CE 117 599 0 13 Jan 2020
Solving inverse-PDE problems with physics-aware neural networks Samira Pakravan Pouria A. Mistani M. Aragon-Calvo Frédéric Gibou AI4CE 42 56 0 10 Jan 2020
Temporal Normalizing Flows G. Both R. Kusters AI4TS 61 12 0 19 Dec 2019
Physics-Informed Neural Networks for Multiphysics Data Assimilation with Application to Subsurface Transport Qizhi He D. Barajas-Solano G. Tartakovsky A. Tartakovsky AI4CE 69 267 0 06 Dec 2019
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators Lu Lu Pengzhan Jin George Karniadakis 254 2,180 0 08 Oct 2019
PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs Xuhui Meng Zhen Li Dongkun Zhang George Karniadakis PINN AI4CE 90 457 0 23 Sep 2019
DL-PDE: Deep-learning based data-driven discovery of partial differential equations from discrete and noisy data Hao Xu Haibin Chang Dongxiao Zhang AI4CE 63 71 0 13 Aug 2019
Learning the Tangent Space of Dynamical Instabilities from Data Antoine Blanchard T. Sapsis 134 8 0 24 Jul 2019