ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2010.08895
  4. Cited By
Fourier Neural Operator for Parametric Partial Differential Equations
v1v2v3 (latest)

Fourier Neural Operator for Parametric Partial Differential Equations

18 October 2020
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Fourier Neural Operator for Parametric Partial Differential Equations"

50 / 1,350 papers shown
Title
LEADS: Learning Dynamical Systems that Generalize Across Environments
LEADS: Learning Dynamical Systems that Generalize Across Environments
Yuan Yin
Ibrahim Ayed
Emmanuel de Bézenac
Nicolas Baskiotis
Patrick Gallinari
OOD
75
34
0
08 Jun 2021
Scalable conditional deep inverse Rosenblatt transports using
  tensor-trains and gradient-based dimension reduction
Scalable conditional deep inverse Rosenblatt transports using tensor-trains and gradient-based dimension reduction
Tiangang Cui
S. Dolgov
O. Zahm
47
15
0
08 Jun 2021
Physics-Guided Discovery of Highly Nonlinear Parametric Partial
  Differential Equations
Physics-Guided Discovery of Highly Nonlinear Parametric Partial Differential Equations
Yingtao Luo
Qiang Liu
Yuntian Chen
Wenbo Hu
Tian Tian
Jun Zhu
DiffM
113
4
0
02 Jun 2021
Choose a Transformer: Fourier or Galerkin
Choose a Transformer: Fourier or Galerkin
Shuhao Cao
90
256
0
31 May 2021
TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems
TNet: A Model-Constrained Tikhonov Network Approach for Inverse Problems
Hai V. Nguyen
T. Bui-Thanh
PINNAI4CE
48
10
0
25 May 2021
Learning Green's Functions of Linear Reaction-Diffusion Equations with
  Application to Fast Numerical Solver
Learning Green's Functions of Linear Reaction-Diffusion Equations with Application to Fast Numerical Solver
Yuankai Teng
Xiaoping Zhang
Zhu Wang
L. Ju
90
14
0
23 May 2021
BubbleNet: Inferring micro-bubble dynamics with semi-physics-informed
  deep learning
BubbleNet: Inferring micro-bubble dynamics with semi-physics-informed deep learning
Hanfeng Zhai
Quan Zhou
G. Hu
PINNAI4CE
51
16
0
15 May 2021
Learning Runge-Kutta Integration Schemes for ODE Simulation and
  Identification
Learning Runge-Kutta Integration Schemes for ODE Simulation and Identification
Said Ouala
L. Debreu
A. Pascual
Bertrand Chapron
F. Collard
L. Gaultier
Ronan Fablet
69
4
0
11 May 2021
FNet: Mixing Tokens with Fourier Transforms
FNet: Mixing Tokens with Fourier Transforms
James Lee-Thorp
Joshua Ainslie
Ilya Eckstein
Santiago Ontanon
134
536
0
09 May 2021
Improving Deep Learning Performance for Predicting Large-Scale
  Porous-Media Flow through Feature Coarsening
Improving Deep Learning Performance for Predicting Large-Scale Porous-Media Flow through Feature Coarsening
B. Yan
D. Harp
Bailian Chen
R. Pawar
AI4CE
57
2
0
08 May 2021
ACORN: Adaptive Coordinate Networks for Neural Scene Representation
ACORN: Adaptive Coordinate Networks for Neural Scene Representation
Julien N. P. Martel
David B. Lindell
Connor Z. Lin
E. R. Chan
M. Monteiro
Gordon Wetzstein
3DPC
88
90
0
06 May 2021
Two-layer neural networks with values in a Banach space
Two-layer neural networks with values in a Banach space
Yury Korolev
95
24
0
05 May 2021
Data-driven discovery of Green's functions with human-understandable
  deep learning
Data-driven discovery of Green's functions with human-understandable deep learning
Nicolas Boullé
Christopher Earls
Alex Townsend
PINNAI4CE
60
60
0
01 May 2021
Inductive biases and Self Supervised Learning in modelling a physical
  heating system
Inductive biases and Self Supervised Learning in modelling a physical heating system
C. Vicas
AI4CE
28
0
0
23 Apr 2021
Mosaic Flows: A Transferable Deep Learning Framework for Solving PDEs on
  Unseen Domains
Mosaic Flows: A Transferable Deep Learning Framework for Solving PDEs on Unseen Domains
Hengjie Wang
R. Planas
Aparna Chandramowlishwaran
Ramin Bostanabad
AI4CE
149
64
0
22 Apr 2021
On the approximation of functions by tanh neural networks
On the approximation of functions by tanh neural networks
Tim De Ryck
S. Lanthaler
Siddhartha Mishra
73
140
0
18 Apr 2021
Applications of physics-informed scientific machine learning in
  subsurface science: A survey
Applications of physics-informed scientific machine learning in subsurface science: A survey
A. Sun
H. Yoon
C. Shih
Zhi Zhong
AI4CE
82
11
0
10 Apr 2021
One-shot learning for solution operators of partial differential
  equations
One-shot learning for solution operators of partial differential equations
Priya Kasimbeg
Haiyang He
Rishikesh Ranade
Jay Pathak
Lu Lu
AI4CE
92
12
0
06 Apr 2021
Deep Learning of Conjugate Mappings
Deep Learning of Conjugate Mappings
J. Bramburger
S. Patterson
J. Nathan Kutz
75
15
0
01 Apr 2021
Latent Space Data Assimilation by using Deep Learning
Latent Space Data Assimilation by using Deep Learning
Mathis Peyron
Anthony Fillion
S. Gürol
Victor Marchais
Serge Gratton
Pierre Boudier
G. Goret
AI4CE
87
47
0
01 Apr 2021
Rethinking Neural Operations for Diverse Tasks
Rethinking Neural Operations for Diverse Tasks
Nicholas Roberts
M. Khodak
Tri Dao
Liam Li
Christopher Ré
Ameet Talwalkar
AI4CE
88
23
0
29 Mar 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
65
13
0
26 Mar 2021
Solving and Learning Nonlinear PDEs with Gaussian Processes
Solving and Learning Nonlinear PDEs with Gaussian Processes
Yifan Chen
Bamdad Hosseini
H. Owhadi
Andrew M. Stuart
93
157
0
24 Mar 2021
Learning the solution operator of parametric partial differential
  equations with physics-informed DeepOnets
Learning the solution operator of parametric partial differential equations with physics-informed DeepOnets
Sizhuang He
Hanwen Wang
P. Perdikaris
AI4CE
104
715
0
19 Mar 2021
Evolutional Deep Neural Network
Evolutional Deep Neural Network
Yifan Du
T. Zaki
85
73
0
18 Mar 2021
Frame-independent vector-cloud neural network for nonlocal constitutive
  modeling on arbitrary grids
Frame-independent vector-cloud neural network for nonlocal constitutive modeling on arbitrary grids
Xueqing Zhou
Jiequn Han
Heng Xiao
78
31
0
11 Mar 2021
Parametric Complexity Bounds for Approximating PDEs with Neural Networks
Parametric Complexity Bounds for Approximating PDEs with Neural Networks
Tanya Marwah
Zachary Chase Lipton
Andrej Risteski
84
19
0
03 Mar 2021
Uncertainty Quantification by Ensemble Learning for Computational
  Optical Form Measurements
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements
L. Hoffmann
I. Fortmeier
Clemens Elster
UQCV
68
28
0
01 Mar 2021
Error Estimates for the Deep Ritz Method with Boundary Penalty
Error Estimates for the Deep Ritz Method with Boundary Penalty
Johannes Müller
Marius Zeinhofer
93
17
0
01 Mar 2021
Meta-Learning Dynamics Forecasting Using Task Inference
Meta-Learning Dynamics Forecasting Using Task Inference
Rui Wang
Robin Walters
Rose Yu
OODAI4TSAI4CE
138
35
0
20 Feb 2021
Deep learning approaches to surrogates for solving the diffusion
  equation for mechanistic real-world simulations
Deep learning approaches to surrogates for solving the diffusion equation for mechanistic real-world simulations
J. Q. Toledo-Marín
Geoffrey C. Fox
J. Sluka
J. Glazier
MedImAI4CE
69
8
0
10 Feb 2021
Novel Deep neural networks for solving Bayesian statistical inverse
Novel Deep neural networks for solving Bayesian statistical inverse
Harbir Antil
H. Elman
Akwum Onwunta
Deepanshu Verma
BDL
21
17
0
08 Feb 2021
Learning elliptic partial differential equations with randomized linear
  algebra
Learning elliptic partial differential equations with randomized linear algebra
Nicolas Boullé
Alex Townsend
50
43
0
31 Jan 2021
Reduced operator inference for nonlinear partial differential equations
Reduced operator inference for nonlinear partial differential equations
E. Qian
Ionut-Gabriel Farcas
Karen E. Willcox
AI4CE
65
39
0
29 Jan 2021
Recurrent Localization Networks applied to the Lippmann-Schwinger
  Equation
Recurrent Localization Networks applied to the Lippmann-Schwinger Equation
Conlain Kelly
S. Kalidindi
AI4CE
36
9
0
29 Jan 2021
Convolutional conditional neural processes for local climate downscaling
Convolutional conditional neural processes for local climate downscaling
Anna Vaughan
Will Tebbutt
J. S. Hosking
Richard Turner
BDL
87
49
0
20 Jan 2021
Hybrid FEM-NN models: Combining artificial neural networks with the
  finite element method
Hybrid FEM-NN models: Combining artificial neural networks with the finite element method
Sebastian K. Mitusch
S. Funke
M. Kuchta
AI4CE
126
99
0
04 Jan 2021
DeepGreen: Deep Learning of Green's Functions for Nonlinear Boundary
  Value Problems
DeepGreen: Deep Learning of Green's Functions for Nonlinear Boundary Value Problems
Craig Gin
D. Shea
Steven L. Brunton
J. Nathan Kutz
90
90
0
31 Dec 2020
Neural Network Approximations for Calabi-Yau Metrics
Neural Network Approximations for Calabi-Yau Metrics
Vishnu Jejjala
D. M. Peña
Challenger Mishra
68
55
0
31 Dec 2020
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
117
153
0
22 Dec 2020
On the eigenvector bias of Fourier feature networks: From regression to
  solving multi-scale PDEs with physics-informed neural networks
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks
Sizhuang He
Hanwen Wang
P. Perdikaris
199
464
0
18 Dec 2020
Algebraically-Informed Deep Networks (AIDN): A Deep Learning Approach to
  Represent Algebraic Structures
Algebraically-Informed Deep Networks (AIDN): A Deep Learning Approach to Represent Algebraic Structures
Mustafa Hajij
Ghada Zamzmi
Matthew Dawson
G. Muller
64
3
0
02 Dec 2020
Importance Weight Estimation and Generalization in Domain Adaptation
  under Label Shift
Importance Weight Estimation and Generalization in Domain Adaptation under Label Shift
Kamyar Azizzadenesheli
OOD
143
13
0
29 Nov 2020
Wide-band butterfly network: stable and efficient inversion via
  multi-frequency neural networks
Wide-band butterfly network: stable and efficient inversion via multi-frequency neural networks
Matthew T.C. Li
L. Demanet
Leonardo Zepeda-Núnez
84
9
0
24 Nov 2020
Discovering Hidden Physics Behind Transport Dynamics
Discovering Hidden Physics Behind Transport Dynamics
Peirong Liu
Lin Tian
Yubo Zhang
S. Aylward
Yueh Z. Lee
Marc Niethammer
DiffMMedIm
32
8
0
24 Nov 2020
Data Assimilation Networks
Data Assimilation Networks
Pierre Boudier
Anthony Fillion
Serge Gratton
S. Gürol
Sixin Zhang
AI4CE
82
12
0
19 Oct 2020
Conditional Sampling with Monotone GANs: from Generative Models to
  Likelihood-Free Inference
Conditional Sampling with Monotone GANs: from Generative Models to Likelihood-Free Inference
Ricardo Baptista
Bamdad Hosseini
Nikola B. Kovachki
Youssef Marzouk
OTGAN
109
24
0
11 Jun 2020
The Random Feature Model for Input-Output Maps between Banach Spaces
The Random Feature Model for Input-Output Maps between Banach Spaces
Nicholas H. Nelsen
Andrew M. Stuart
103
144
0
20 May 2020
Integrating Scientific Knowledge with Machine Learning for Engineering
  and Environmental Systems
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
J. Willard
X. Jia
Shaoming Xu
M. Steinbach
Vipin Kumar
AI4CE
158
414
0
10 Mar 2020
Hamiltonian neural networks for solving equations of motion
Hamiltonian neural networks for solving equations of motion
M. Mattheakis
David Sondak
Akshunna S. Dogra
P. Protopapas
108
59
0
29 Jan 2020
Previous
123...252627