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Smooth and Sparse Latent Dynamics in Operator Learning with Jerk
  Regularization

Smooth and Sparse Latent Dynamics in Operator Learning with Jerk Regularization

23 February 2024
Xiaoyu Xie
S. Mowlavi
M. Benosman
    AI4CE
ArXiv (abs)PDFHTML

Papers citing "Smooth and Sparse Latent Dynamics in Operator Learning with Jerk Regularization"

23 / 23 papers shown
Title
Self-Supervised Learning with Lie Symmetries for Partial Differential
  Equations
Self-Supervised Learning with Lie Symmetries for Partial Differential Equations
Grégoire Mialon
Q. Garrido
Hannah Lawrence
Danyal Rehman
Yann LeCun
B. Kiani
SSL
80
26
0
11 Jul 2023
Operator Learning with Neural Fields: Tackling PDEs on General
  Geometries
Operator Learning with Neural Fields: Tackling PDEs on General Geometries
Louis Serrano
Lise Le Boudec
Armand K. Koupai
Thomas X. Wang
Yuan Yin
Jean-Noel Vittaut
Patrick Gallinari
AI4CE
82
42
0
12 Jun 2023
Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For
  Advection-Dominated Systems
Evolve Smoothly, Fit Consistently: Learning Smooth Latent Dynamics For Advection-Dominated Systems
Z. Y. Wan
Leonardo Zepeda-Núñez
Anudhyan Boral
Fei Sha
BDLAI4CE
72
13
0
25 Jan 2023
Physics-Informed Deep Neural Operator Networks
Physics-Informed Deep Neural Operator Networks
S. Goswami
Aniruddha Bora
Yue Yu
George Karniadakis
PINNAI4CE
90
108
0
08 Jul 2022
NOMAD: Nonlinear Manifold Decoders for Operator Learning
NOMAD: Nonlinear Manifold Decoders for Operator Learning
Jacob H. Seidman
Georgios Kissas
P. Perdikaris
George J. Pappas
AI4CE
83
77
0
07 Jun 2022
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural
  Representations
CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations
Julius Berner
Jinxu Xiang
D. Cho
Yue Chang
G. Pershing
H. Maia
Maurizio M. Chiaramonte
Kevin Carlberg
E. Grinspun
AI4CE
91
44
0
06 Jun 2022
FourCastNet: A Global Data-driven High-resolution Weather Model using
  Adaptive Fourier Neural Operators
FourCastNet: A Global Data-driven High-resolution Weather Model using Adaptive Fourier Neural Operators
Jaideep Pathak
Shashank Subramanian
P. Harrington
S. Raja
Ashesh Chattopadhyay
...
Zong-Yi Li
Kamyar Azizzadenesheli
Pedram Hassanzadeh
K. Kashinath
Anima Anandkumar
AI4Cl
242
711
0
22 Feb 2022
Learning Operators with Coupled Attention
Learning Operators with Coupled Attention
Georgios Kissas
Jacob H. Seidman
Leonardo Ferreira Guilhoto
V. Preciado
George J. Pappas
P. Perdikaris
81
113
0
04 Jan 2022
Physics-Informed Neural Operator for Learning Partial Differential
  Equations
Physics-Informed Neural Operator for Learning Partial Differential Equations
Zong-Yi Li
Hongkai Zheng
Nikola B. Kovachki
David Jin
Haoxuan Chen
Burigede Liu
Kamyar Azizzadenesheli
Anima Anandkumar
AI4CE
121
424
0
06 Nov 2021
Physics-informed Convolutional Neural Networks for Temperature Field
  Prediction of Heat Source Layout without Labeled Data
Physics-informed Convolutional Neural Networks for Temperature Field Prediction of Heat Source Layout without Labeled Data
Xiaoyu Zhao
Zhiqiang Gong
Yunyang Zhang
Wen Yao
Xiaoqian Chen
OODAI4CE
120
95
0
26 Sep 2021
PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving
  Spatiotemporal PDEs
PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs
Pu Ren
Chengping Rao
Yang Liu
Jianxun Wang
Hao Sun
DiffMAI4CE
115
204
0
26 Jun 2021
Scalars are universal: Equivariant machine learning, structured like
  classical physics
Scalars are universal: Equivariant machine learning, structured like classical physics
Soledad Villar
D. Hogg
Kate Storey-Fisher
Weichi Yao
Ben Blum-Smith
PINNAI4CE
73
136
0
11 Jun 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review
Physics-informed neural networks (PINNs) for fluid mechanics: A review
Shengze Cai
Zhiping Mao
Zhicheng Wang
Minglang Yin
George Karniadakis
PINNAI4CE
88
1,209
0
20 May 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
102
710
0
19 Mar 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
509
2,453
0
18 Oct 2020
Learning Mesh-Based Simulation with Graph Networks
Learning Mesh-Based Simulation with Graph Networks
Tobias Pfaff
Meire Fortunato
Alvaro Sanchez-Gonzalez
Peter W. Battaglia
AI4CE
82
806
0
07 Oct 2020
Implicit Neural Representations with Periodic Activation Functions
Implicit Neural Representations with Periodic Activation Functions
Vincent Sitzmann
Julien N. P. Martel
Alexander W. Bergman
David B. Lindell
Gordon Wetzstein
AI4TS
172
2,577
0
17 Jun 2020
DeepONet: Learning nonlinear operators for identifying differential
  equations based on the universal approximation theorem of operators
DeepONet: Learning nonlinear operators for identifying differential equations based on the universal approximation theorem of operators
Lu Lu
Pengzhan Jin
George Karniadakis
248
2,158
0
08 Oct 2019
Machine Learning for Fluid Mechanics
Machine Learning for Fluid Mechanics
Steven Brunton
B. R. Noack
Petros Koumoutsakos
AI4CEPINN
91
2,128
0
27 May 2019
DeepSDF: Learning Continuous Signed Distance Functions for Shape
  Representation
DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation
Jeong Joon Park
Peter R. Florence
Julian Straub
Richard Newcombe
S. Lovegrove
3DV
133
3,707
0
16 Jan 2019
Neural Ordinary Differential Equations
Neural Ordinary Differential Equations
T. Chen
Yulia Rubanova
J. Bettencourt
David Duvenaud
AI4CE
452
5,168
0
19 Jun 2018
Sigmoid-Weighted Linear Units for Neural Network Function Approximation
  in Reinforcement Learning
Sigmoid-Weighted Linear Units for Neural Network Function Approximation in Reinforcement Learning
Stefan Elfwing
E. Uchibe
Kenji Doya
141
1,746
0
10 Feb 2017
Delving Deep into Rectifiers: Surpassing Human-Level Performance on
  ImageNet Classification
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
VLM
355
18,654
0
06 Feb 2015
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