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2405.01680
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Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations
2 May 2024
Nima Hosseini Dashtbayaz
G. Farhani
Boyu Wang
Charles Ling
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Papers citing
"Physics-Informed Neural Networks: Minimizing Residual Loss with Wide Networks and Effective Activations"
16 / 16 papers shown
Title
Dual-Balancing for Physics-Informed Neural Networks
Chenhong Zhou
Jie Chen
Zaifeng Yang
Ching Eng Png
PINN
AI4CE
90
0
0
16 May 2025
Respecting causality is all you need for training physics-informed neural networks
Sizhuang He
Shyam Sankaran
P. Perdikaris
PINN
CML
AI4CE
131
200
0
14 Mar 2022
Periodic Activation Functions Induce Stationarity
Lassi Meronen
Martin Trapp
Arno Solin
BDL
47
21
0
26 Oct 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks
Jian Cheng Wong
C. Ooi
Abhishek Gupta
Yew-Soon Ong
AI4CE
PINN
SSL
56
79
0
20 Sep 2021
Physics-informed neural networks (PINNs) for fluid mechanics: A review
Shengze Cai
Zhiping Mao
Zhicheng Wang
Minglang Yin
George Karniadakis
PINN
AI4CE
66
1,183
0
20 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
484
2,397
0
18 Oct 2020
On the linearity of large non-linear models: when and why the tangent kernel is constant
Chaoyue Liu
Libin Zhu
M. Belkin
104
141
0
02 Oct 2020
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism
L. McClenny
U. Braga-Neto
PINN
72
458
0
07 Sep 2020
When and why PINNs fail to train: A neural tangent kernel perspective
Sizhuang He
Xinling Yu
P. Perdikaris
123
908
0
28 Jul 2020
A Method for Representing Periodic Functions and Enforcing Exactly Periodic Boundary Conditions with Deep Neural Networks
S. Dong
Naxian Ni
76
137
0
15 Jul 2020
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks
Colby Wight
Jia Zhao
72
224
0
09 Jul 2020
Implicit Neural Representations with Periodic Activation Functions
Vincent Sitzmann
Julien N. P. Martel
Alexander W. Bergman
David B. Lindell
Gordon Wetzstein
AI4TS
125
2,548
0
17 Jun 2020
Understanding and mitigating gradient pathologies in physics-informed neural networks
Sizhuang He
Yujun Teng
P. Perdikaris
AI4CE
PINN
89
294
0
13 Jan 2020
Width Provably Matters in Optimization for Deep Linear Neural Networks
S. Du
Wei Hu
57
95
0
24 Jan 2019
On the Spectral Bias of Neural Networks
Nasim Rahaman
A. Baratin
Devansh Arpit
Felix Dräxler
Min Lin
Fred Hamprecht
Yoshua Bengio
Aaron Courville
131
1,436
0
22 Jun 2018
Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations
M. Raissi
P. Perdikaris
George Karniadakis
PINN
AI4CE
75
924
0
28 Nov 2017
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