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Neural Networks Trained to Solve Differential Equations Learn General
  Representations

Neural Networks Trained to Solve Differential Equations Learn General Representations

29 June 2018
M. Magill
F. Qureshi
H. W. Haan
ArXivPDFHTML

Papers citing "Neural Networks Trained to Solve Differential Equations Learn General Representations"

13 / 13 papers shown
Title
Approximation of Solution Operators for High-dimensional PDEs
Approximation of Solution Operators for High-dimensional PDEs
Nathan Gaby
Xiaojing Ye
30
0
0
18 Jan 2024
Revisiting Hidden Representations in Transfer Learning for Medical
  Imaging
Revisiting Hidden Representations in Transfer Learning for Medical Imaging
Dovile Juodelyte
Amelia Jiménez-Sánchez
V. Cheplygina
OOD
19
1
0
16 Feb 2023
When Physics Meets Machine Learning: A Survey of Physics-Informed
  Machine Learning
When Physics Meets Machine Learning: A Survey of Physics-Informed Machine Learning
Chuizheng Meng
Sungyong Seo
Defu Cao
Sam Griesemer
Yan Liu
PINN
AI4CE
51
57
0
31 Mar 2022
Interpolating between BSDEs and PINNs: deep learning for elliptic and
  parabolic boundary value problems
Interpolating between BSDEs and PINNs: deep learning for elliptic and parabolic boundary value problems
Nikolas Nusken
Lorenz Richter
PINN
DiffM
31
27
0
07 Dec 2021
Feature Engineering with Regularity Structures
Feature Engineering with Regularity Structures
I. Chevyrev
A. Gerasimovičs
H. Weber
32
10
0
12 Aug 2021
Elvet -- a neural network-based differential equation and variational
  problem solver
Elvet -- a neural network-based differential equation and variational problem solver
Jack Y. Araz
J. C. Criado
M. Spannowsky
26
13
0
26 Mar 2021
An overview on deep learning-based approximation methods for partial
  differential equations
An overview on deep learning-based approximation methods for partial differential equations
C. Beck
Martin Hutzenthaler
Arnulf Jentzen
Benno Kuckuck
30
146
0
22 Dec 2020
Physics-informed Neural-Network Software for Molecular Dynamics
  Applications
Physics-informed Neural-Network Software for Molecular Dynamics Applications
Taufeq Mohammed Razakh
Beibei Wang
Shane Jackson
R. Kalia
A. Nakano
K. Nomura
P. Vashishta
PINN
24
11
0
06 Nov 2020
Space-time deep neural network approximations for high-dimensional
  partial differential equations
Space-time deep neural network approximations for high-dimensional partial differential equations
F. Hornung
Arnulf Jentzen
Diyora Salimova
AI4CE
29
19
0
03 Jun 2020
Uniform error estimates for artificial neural network approximations for
  heat equations
Uniform error estimates for artificial neural network approximations for heat equations
Lukas Gonon
Philipp Grohs
Arnulf Jentzen
David Kofler
David Siska
29
34
0
20 Nov 2019
Space-time error estimates for deep neural network approximations for
  differential equations
Space-time error estimates for deep neural network approximations for differential equations
Philipp Grohs
F. Hornung
Arnulf Jentzen
Philipp Zimmermann
29
33
0
11 Aug 2019
Deep splitting method for parabolic PDEs
Deep splitting method for parabolic PDEs
C. Beck
S. Becker
Patrick Cheridito
Arnulf Jentzen
Ariel Neufeld
23
125
0
08 Jul 2019
Transfusion: Understanding Transfer Learning for Medical Imaging
Transfusion: Understanding Transfer Learning for Medical Imaging
M. Raghu
Chiyuan Zhang
Jon M. Kleinberg
Samy Bengio
MedIm
30
972
0
14 Feb 2019
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