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1907.04502
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DeepXDE: A deep learning library for solving differential equations
10 July 2019
Lu Lu
Xuhui Meng
Zhiping Mao
George Karniadakis
PINN
AI4CE
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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
2,179
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
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