Papers
Communities
Events
Blog
Pricing
Search
Open menu
Home
Papers
2106.14103
Cited By
PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs
26 June 2021
Pu Ren
Chengping Rao
Yang Liu
Jianxun Wang
Hao-Lun Sun
DiffM
AI4CE
Re-assign community
ArXiv
PDF
HTML
Papers citing
"PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs"
19 / 19 papers shown
Title
Sensitivity-Constrained Fourier Neural Operators for Forward and Inverse Problems in Parametric Differential Equations
Abdolmehdi Behroozi
Chaopeng Shen and
Daniel Kifer
AI4CE
13
0
0
13 May 2025
PeSANet: Physics-encoded Spectral Attention Network for Simulating PDE-Governed Complex Systems
Han Wan
Rui Zhang
Qi Wang
Y. Liu
Hao Sun
PINN
33
0
0
03 May 2025
PIMRL: Physics-Informed Multi-Scale Recurrent Learning for Spatiotemporal Prediction
Han Wan
Qi Wang
Hao Sun
Hao Sun
AI4CE
46
0
0
13 Mar 2025
Sampling-based Distributed Training with Message Passing Neural Network
P. Kakka
Sheel Nidhan
Rishikesh Ranade
Jay Pathak
J. MacArt
GNN
75
3
0
20 Feb 2025
PhyMPGN: Physics-encoded Message Passing Graph Network for spatiotemporal PDE systems
Bocheng Zeng
Qi Wang
M. Yan
Y. Liu
Ruizhi Chengze
Yi Zhang
Hongsheng Liu
Zidong Wang
Hao Sun
AI4CE
21
3
0
02 Oct 2024
Discovery and inversion of the viscoelastic wave equation in inhomogeneous media
Su Chen
Yi Ding
Hiroe Miyake
Xiaojun Li
34
0
0
27 Sep 2024
A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: efficient mapping of concrete microstructures to its fracture properties
Rasoul Najafi Koopas
Shahed Rezaei
N. Rauter
Richard Ostwald
R. Lammering
AI4CE
31
2
0
22 Jul 2024
A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains
Yusuke Yamazaki
Ali Harandi
Mayu Muramatsu
A. Viardin
Markus Apel
T. Brepols
Stefanie Reese
Shahed Rezaei
AI4CE
26
12
0
21 May 2024
Time integration schemes based on neural networks for solving partial differential equations on coarse grids
Xinxin Yan
Zhideng Zhou
Xiaohan Cheng
Xiaolei Yang
AI4TS
AI4CE
13
0
0
16 Oct 2023
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
18
9
0
08 Oct 2023
Partial Differential Equations Meet Deep Neural Networks: A Survey
Shudong Huang
Wentao Feng
Chenwei Tang
Jiancheng Lv
AI4CE
AIMat
11
17
0
27 Oct 2022
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain
Pu Ren
Chengping Rao
Su Chen
Jian-Xun Wang
Hao-Lun Sun
Yang Liu
18
40
0
25 Oct 2022
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
16
45
0
09 May 2022
Hard Encoding of Physics for Learning Spatiotemporal Dynamics
Chengping Rao
Hao-Lun Sun
Yang Liu
PINN
AI4CE
21
9
0
02 May 2021
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
203
2,272
0
18 Oct 2020
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications
E. Samaniego
C. Anitescu
S. Goswami
Vien Minh Nguyen-Thanh
Hongwei Guo
Khader M. Hamdia
Timon Rabczuk
X. Zhuang
PINN
AI4CE
145
1,333
0
27 Aug 2019
Geometric deep learning: going beyond Euclidean data
M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
P. Vandergheynst
GNN
231
3,230
0
24 Nov 2016
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network
Wenzhe Shi
Jose Caballero
Ferenc Huszár
J. Totz
Andrew P. Aitken
Rob Bishop
Daniel Rueckert
Zehan Wang
SupR
190
5,163
0
16 Sep 2016
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
Xingjian Shi
Zhourong Chen
Hao Wang
Dit-Yan Yeung
W. Wong
W. Woo
201
7,884
0
13 Jun 2015
1