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PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep
  Network

PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network

30 November 2018
Zichao Long
Yiping Lu
Bin Dong
    AI4CE
ArXivPDFHTML

Papers citing "PDE-Net 2.0: Learning PDEs from Data with A Numeric-Symbolic Hybrid Deep Network"

50 / 84 papers shown
Title
UniSymNet: A Unified Symbolic Network Guided by Transformer
UniSymNet: A Unified Symbolic Network Guided by Transformer
Xinxin Li
Juan Zhang
Da Li
Xingyu Liu
Jin Xu
Junping Yin
29
0
0
09 May 2025
PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems
PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems
Han Wan
Rui Zhang
Qi Wang
Y. Liu
Hao Sun
PINN
45
0
0
03 May 2025
Plug-and-Play Physics-informed Learning using Uncertainty Quantified Port-Hamiltonian Models
Plug-and-Play Physics-informed Learning using Uncertainty Quantified Port-Hamiltonian Models
Kaiyuan Tan
Peilun Li
J. Wang
Thomas Beckers
AI4CE
19
0
0
24 Apr 2025
PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Spatiotemporal Prediction
PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Spatiotemporal Prediction
Han Wan
Qi Wang
Hao Sun
Hao Sun
AI4CE
54
0
0
13 Mar 2025
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
Data-Efficient Kernel Methods for Learning Differential Equations and Their Solution Operators: Algorithms and Error Analysis
Yasamin Jalalian
Juan Felipe Osorio Ramirez
Alexander W. Hsu
Bamdad Hosseini
H. Owhadi
43
0
0
02 Mar 2025
Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks
Adaptive parameters identification for nonlinear dynamics using deep permutation invariant networks
Mouad Elaarabi
Domenico Borzacchiello
Yves Le Guennec
Philippe Le Bot
Sebastien Comas-Cardona
78
0
0
20 Jan 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks
Cyrus Neary
Nathan Tsao
Ufuk Topcu
74
1
0
15 Dec 2024
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems
Xin Li
Jingdong Zhang
Qunxi Zhu
Chengli Zhao
Xue Zhang
Xiaojun Duan
Wei Lin
47
3
0
19 May 2024
Towards General Neural Surrogate Solvers with Specialized Neural
  Accelerators
Towards General Neural Surrogate Solvers with Specialized Neural Accelerators
Chenkai Mao
Robert Lupoiu
Tianxiang Dai
Mingkun Chen
Jonathan A. Fan
AI4CE
36
4
0
02 May 2024
Data-Driven Discovery of PDEs via the Adjoint Method
Data-Driven Discovery of PDEs via the Adjoint Method
Mohsen Sadr
Tony Tohme
Kamal Youcef-Toumi
PINN
19
1
0
30 Jan 2024
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi
  Consolidation Equation: Forward and Inverse Problems
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems
Biao Yuan
Ana Heitor
He Wang
Xiaohui Chen
AI4CE
PINN
31
1
0
08 Jan 2024
Hybrid Modeling Design Patterns
Hybrid Modeling Design Patterns
Maja Rudolph
Stefan Kurz
Barbara Rakitsch
AI4CE
31
8
0
29 Dec 2023
GIT-Net: Generalized Integral Transform for Operator Learning
GIT-Net: Generalized Integral Transform for Operator Learning
Chao Wang
Alexandre H. Thiery
AI4CE
29
0
0
05 Dec 2023
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for
  Machine Learning and Process-based Hydrology
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology
Qingsong Xu
Yilei Shi
Jonathan Bamber
Ye Tuo
Ralf Ludwig
Xiao Xiang Zhu
AI4CE
20
10
0
08 Oct 2023
A Spectral Approach for Learning Spatiotemporal Neural Differential
  Equations
A Spectral Approach for Learning Spatiotemporal Neural Differential Equations
Mingtao Xia
Xiangting Li
Qijing Shen
Tom Chou
13
0
0
28 Sep 2023
Latent assimilation with implicit neural representations for unknown
  dynamics
Latent assimilation with implicit neural representations for unknown dynamics
Zhuoyuan Li
Bin Dong
Pingwen Zhang
AI4CE
24
3
0
18 Sep 2023
Learning to simulate partially known spatio-temporal dynamics with
  trainable difference operators
Learning to simulate partially known spatio-temporal dynamics with trainable difference operators
Xiang Huang
Zhuoyuan Li
Hongsheng Liu
Zidong Wang
Hongye Zhou
Bin Dong
Bei Hua
AI4TS
AI4CE
29
1
0
26 Jul 2023
Flow Map Learning for Unknown Dynamical Systems: Overview,
  Implementation, and Benchmarks
Flow Map Learning for Unknown Dynamical Systems: Overview, Implementation, and Benchmarks
V. Churchill
D. Xiu
AI4CE
22
10
0
20 Jul 2023
A Bayesian Framework for learning governing Partial Differential
  Equation from Data
A Bayesian Framework for learning governing Partial Differential Equation from Data
K. More
Tapas Tripura
R. Nayek
S. Chakraborty
16
10
0
08 Jun 2023
Discovering Causal Relations and Equations from Data
Discovering Causal Relations and Equations from Data
Gustau Camps-Valls
Andreas Gerhardus
Urmi Ninad
Gherardo Varando
Georg Martius
E. Balaguer-Ballester
Ricardo Vinuesa
Emiliano Díaz
L. Zanna
Jakob Runge
PINN
AI4Cl
AI4CE
CML
35
72
0
21 May 2023
Pseudo-Hamiltonian neural networks for learning partial differential
  equations
Pseudo-Hamiltonian neural networks for learning partial differential equations
Sølve Eidnes
K. Lye
18
10
0
27 Apr 2023
Neural Delay Differential Equations: System Reconstruction and Image
  Classification
Neural Delay Differential Equations: System Reconstruction and Image Classification
Qunxi Zhu
Yao Guo
Wei Lin
15
31
0
11 Apr 2023
Machine Learning for Partial Differential Equations
Machine Learning for Partial Differential Equations
Steven L. Brunton
J. Nathan Kutz
AI4CE
37
20
0
30 Mar 2023
CONFIDE: Contextual Finite Differences Modelling of PDEs
CONFIDE: Contextual Finite Differences Modelling of PDEs
Ori Linial
Orly Avner
Dotan Di Castro
38
0
0
28 Mar 2023
GNN-based physics solver for time-independent PDEs
GNN-based physics solver for time-independent PDEs
R. J. Gladstone
H. Rahmani
V. Suryakumar
Hadi Meidani
M. DÉlia
A. Zareei
AI4CE
20
15
0
28 Mar 2023
Neural Partial Differential Equations with Functional Convolution
Neural Partial Differential Equations with Functional Convolution
Z. Wu
Xingzhe He
Yijun Li
Cheng Yang
Rui Liu
S. Xiong
Bo Zhu
23
1
0
10 Mar 2023
Physics-Informed Neural Networks for Prognostics and Health Management
  of Lithium-Ion Batteries
Physics-Informed Neural Networks for Prognostics and Health Management of Lithium-Ion Batteries
Pengfei Wen
Z. Ye
Yong Li
Shaowei Chen
Pu Xie
Shuai Zhao
30
35
0
02 Jan 2023
Interpretability and accessibility of machine learning in selected food
  processing, agriculture and health applications
Interpretability and accessibility of machine learning in selected food processing, agriculture and health applications
N. Ranasinghe
A. Ramanan
S. Fernando
P. N. Hameed
D. Herath
T. Malepathirana
P. Suganthan
M. Niranjan
Saman K. Halgamuge
8
2
0
30 Nov 2022
Discovering ordinary differential equations that govern time-series
Discovering ordinary differential equations that govern time-series
Soren Becker
M. Klein
Alexander Neitz
Giambattista Parascandolo
Niki Kilbertus
AI4TS
19
4
0
05 Nov 2022
DISCOVER: Deep identification of symbolically concise open-form PDEs via
  enhanced reinforcement-learning
DISCOVER: Deep identification of symbolically concise open-form PDEs via enhanced reinforcement-learning
Mengge Du
Yuntian Chen
Dong-juan Zhang
28
0
0
04 Oct 2022
Minimax Optimal Kernel Operator Learning via Multilevel Training
Minimax Optimal Kernel Operator Learning via Multilevel Training
Jikai Jin
Yiping Lu
Jose H. Blanchet
Lexing Ying
20
11
0
28 Sep 2022
Data-driven, multi-moment fluid modeling of Landau damping
Data-driven, multi-moment fluid modeling of Landau damping
Wenjie Cheng
H. Fu
Liang Wang
C. Dong
Yaqiu Jin
M. Jiang
Jiayu Ma
Yilan Qin
Kexin Liu
PINN
AI4CE
22
12
0
10 Sep 2022
D-CIPHER: Discovery of Closed-form Partial Differential Equations
D-CIPHER: Discovery of Closed-form Partial Differential Equations
Krzysztof Kacprzyk
Zhaozhi Qian
M. Schaar
AI4CE
21
1
0
21 Jun 2022
Sobolev Acceleration and Statistical Optimality for Learning Elliptic
  Equations via Gradient Descent
Sobolev Acceleration and Statistical Optimality for Learning Elliptic Equations via Gradient Descent
Yiping Lu
Jose H. Blanchet
Lexing Ying
35
7
0
15 May 2022
Automated differential equation solver based on the parametric
  approximation optimization
Automated differential equation solver based on the parametric approximation optimization
A. Hvatov
Tatiana Tikhonova
14
4
0
11 May 2022
Multi-resolution partial differential equations preserved learning
  framework for spatiotemporal dynamics
Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics
Xin-Yang Liu
Min Zhu
Lu Lu
Hao Sun
Jian-Xun Wang
PINN
AI4CE
28
45
0
09 May 2022
Learning time-dependent PDE solver using Message Passing Graph Neural
  Networks
Learning time-dependent PDE solver using Message Passing Graph Neural Networks
Pourya Pilva
A. Zareei
AI4CE
25
7
0
15 Apr 2022
PARC: Physics-Aware Recurrent Convolutional Neural Networks to
  Assimilate Meso-scale Reactive Mechanics of Energetic Materials
PARC: Physics-Aware Recurrent Convolutional Neural Networks to Assimilate Meso-scale Reactive Mechanics of Energetic Materials
Phong C. H. Nguyen
Y. Nguyen
Joseph B. Choi
P. Seshadri
H. Udaykumar
Stephen Seung-Yeob Baek
AI4CE
16
16
0
04 Apr 2022
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
36
55
0
31 Mar 2022
Online Weak-form Sparse Identification of Partial Differential Equations
Online Weak-form Sparse Identification of Partial Differential Equations
Daniel Messenger
E. Dall’Anese
David M. Bortz
41
13
0
08 Mar 2022
Robust Modeling of Unknown Dynamical Systems via Ensemble Averaged
  Learning
Robust Modeling of Unknown Dynamical Systems via Ensemble Averaged Learning
V. Churchill
Steve Manns
Zhen Chen
D. Xiu
AI4CE
26
9
0
07 Mar 2022
Modeling unknown dynamical systems with hidden parameters
Modeling unknown dynamical systems with hidden parameters
Xiaohan Fu
Weize Mao
L. Chang
D. Xiu
16
5
0
03 Feb 2022
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded
  Learning
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
Chengping Rao
Pu Ren
Yang Liu
Hao-Lun Sun
AI4CE
43
26
0
28 Jan 2022
Characteristic Neural Ordinary Differential Equations
Characteristic Neural Ordinary Differential Equations
Xingzi Xu
Ali Hasan
Khalil Elkhalil
Jie Ding
Vahid Tarokh
BDL
23
3
0
25 Nov 2021
NeuralPDE: Modelling Dynamical Systems from Data
NeuralPDE: Modelling Dynamical Systems from Data
Andrzej Dulny
Andreas Hotho
Anna Krause
AI4CE
24
11
0
15 Nov 2021
DeepParticle: learning invariant measure by a deep neural network
  minimizing Wasserstein distance on data generated from an interacting
  particle method
DeepParticle: learning invariant measure by a deep neural network minimizing Wasserstein distance on data generated from an interacting particle method
Zhongjian Wang
Jack Xin
Zhiwen Zhang
39
15
0
02 Nov 2021
Short-term traffic prediction using physics-aware neural networks
Short-term traffic prediction using physics-aware neural networks
M. Pereira
Annika Lang
Balázs Kulcsár
28
21
0
21 Sep 2021
Physics-integrated hybrid framework for model form error identification
  in nonlinear dynamical systems
Physics-integrated hybrid framework for model form error identification in nonlinear dynamical systems
Shailesh Garg
S. Chakraborty
B. Hazra
41
20
0
01 Sep 2021
Designing Rotationally Invariant Neural Networks from PDEs and
  Variational Methods
Designing Rotationally Invariant Neural Networks from PDEs and Variational Methods
Tobias Alt
Karl Schrader
Joachim Weickert
Pascal Peter
M. Augustin
22
4
0
31 Aug 2021
Data-Driven Constitutive Relation Reveals Scaling Law for Hydrodynamic
  Transport Coefficients
Data-Driven Constitutive Relation Reveals Scaling Law for Hydrodynamic Transport Coefficients
Candi Zheng
Yang Wang
Shiying Chen
19
4
0
01 Aug 2021
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