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2211.08064
Cited By
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications
15 November 2022
Zhongkai Hao
Songming Liu
Yichi Zhang
Chengyang Ying
Yao Feng
Hang Su
Jun Zhu
PINN
AI4CE
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Papers citing
"Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications"
35 / 35 papers shown
Title
Receding Hamiltonian-Informed Optimal Neural Control and State Estimation for Closed-Loop Dynamical Systems
Josue N. Rivera
Dengfeng Sun
28
0
0
02 Nov 2024
Gradient Flow Based Phase-Field Modeling Using Separable Neural Networks
R. Mattey
Susanta Ghosh
AI4CE
40
1
0
09 May 2024
Neural Parameter Regression for Explicit Representations of PDE Solution Operators
Konrad Mundinger
Max Zimmer
S. Pokutta
44
0
0
19 Mar 2024
From Spectra to Biophysical Insights: End-to-End Learning with a Biased Radiative Transfer Model
Yihang She
Clement Atzberger
Andrew Blake
Srinivasan Keshav
16
0
0
05 Mar 2024
Discovering Artificial Viscosity Models for Discontinuous Galerkin Approximation of Conservation Laws using Physics-Informed Machine Learning
Matteo Caldana
P. Antonietti
Luca Dede'
AI4CE
PINN
27
1
0
26 Feb 2024
Physics-Informed Computer Vision: A Review and Perspectives
C. Banerjee
Kien Nguyen
Clinton Fookes
G. Karniadakis
PINN
AI4CE
34
28
0
29 May 2023
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning
Jun Shu
Xiang Yuan
Deyu Meng
Zongben Xu
28
4
0
13 May 2023
Probing optimisation in physics-informed neural networks
Nayara Fonseca
V. Guidetti
Will Trojak
31
1
0
27 Mar 2023
Equivariant Energy-Guided SDE for Inverse Molecular Design
Fan Bao
Min Zhao
Zhongkai Hao
Pei‐Yun Li
Chongxuan Li
Jun Zhu
DiffM
187
63
0
30 Sep 2022
Fourier Neural Operator with Learned Deformations for PDEs on General Geometries
Zong-Yi Li
Daniel Zhengyu Huang
Burigede Liu
Anima Anandkumar
AI4CE
116
249
0
11 Jul 2022
D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactions
Sammy Christen
Muhammed Kocabas
Emre Aksan
Jemin Hwangbo
Jie Song
Otmar Hilliges
108
104
0
01 Dec 2021
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
305
7,434
0
11 Nov 2021
Solving PDE-constrained Control Problems Using Operator Learning
Rakhoon Hwang
Jae Yong Lee
J. Shin
H. Hwang
AI4CE
114
43
0
09 Nov 2021
Improved architectures and training algorithms for deep operator networks
Sifan Wang
Hanwen Wang
P. Perdikaris
AI4CE
49
105
0
04 Oct 2021
Multiwavelet-based Operator Learning for Differential Equations
Gaurav Gupta
Xiongye Xiao
P. Bogdan
126
200
0
28 Sep 2021
Arbitrary-Depth Universal Approximation Theorems for Operator Neural Networks
Annan Yu
Chloe Becquey
Diana Halikias
Matthew Esmaili Mallory
Alex Townsend
59
8
0
23 Sep 2021
Physics-based Deep Learning
Nils Thuerey
Philipp Holl
P. Holl
Patrick Schnell
Felix Trost
Kiwon Um
P. Schnell
F. Trost
PINN
AI4CE
53
92
0
11 Sep 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations
Benjamin Moseley
Andrew Markham
T. Nissen‐Meyer
PINN
45
209
0
16 Jul 2021
Meta-learning PINN loss functions
Apostolos F. Psaros
Kenji Kawaguchi
George Karniadakis
PINN
41
97
0
12 Jul 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges
M. Bronstein
Joan Bruna
Taco S. Cohen
Petar Velivcković
GNN
174
1,104
0
27 Apr 2021
Efficient training of physics-informed neural networks via importance sampling
M. A. Nabian
R. J. Gladstone
Hadi Meidani
DiffM
PINN
71
222
0
26 Apr 2021
Parallel Physics-Informed Neural Networks via Domain Decomposition
K. Shukla
Ameya Dilip Jagtap
George Karniadakis
PINN
101
274
0
20 Apr 2021
Physics-informed neural networks with hard constraints for inverse design
Lu Lu
R. Pestourie
Wenjie Yao
Zhicheng Wang
F. Verdugo
Steven G. Johnson
PINN
39
494
0
09 Feb 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks
Sifan Wang
Hanwen Wang
P. Perdikaris
131
438
0
18 Dec 2020
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
205
2,282
0
18 Oct 2020
Multi-scale Deep Neural Network (MscaleDNN) for Solving Poisson-Boltzmann Equation in Complex Domains
Ziqi Liu
Wei Cai
Zhi-Qin John Xu
AI4CE
211
122
0
22 Jul 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition
E. Kharazmi
Zhongqiang Zhang
George Karniadakis
125
508
0
11 Mar 2020
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems
J. Willard
X. Jia
Shaoming Xu
M. Steinbach
Vipin Kumar
AI4CE
91
387
0
10 Mar 2020
Lagrangian Neural Networks
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
PINN
130
424
0
10 Mar 2020
Measurement-based adaptation protocol with quantum reinforcement learning in a Rigetti quantum computer
Julio Olivares-Sánchez
J. Casanova
Enrique Solano
L. Lamata
24
36
0
19 Nov 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation
Jiaxuan You
Bowen Liu
Rex Ying
Vijay S. Pande
J. Leskovec
GNN
203
885
0
07 Jun 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong Jin
Regina Barzilay
Tommi Jaakkola
224
1,338
0
12 Feb 2018
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
C. Qi
Hao Su
Kaichun Mo
Leonidas J. Guibas
3DH
3DPC
3DV
PINN
222
14,099
0
02 Dec 2016
Interaction Networks for Learning about Objects, Relations and Physics
Peter W. Battaglia
Razvan Pascanu
Matthew Lai
Danilo Jimenez Rezende
Koray Kavukcuoglu
AI4CE
OCL
PINN
GNN
278
1,400
0
01 Dec 2016
Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes
Ohad Shamir
Tong Zhang
101
570
0
08 Dec 2012
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