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Characterizing possible failure modes in physics-informed neural
  networks

Characterizing possible failure modes in physics-informed neural networks

2 September 2021
Aditi S. Krishnapriyan
A. Gholami
Shandian Zhe
Robert M. Kirby
Michael W. Mahoney
    PINN
    AI4CE
ArXivPDFHTML

Papers citing "Characterizing possible failure modes in physics-informed neural networks"

50 / 325 papers shown
Title
Neural PDE Solvers for Irregular Domains
Neural PDE Solvers for Irregular Domains
Biswajit Khara
Ethan Herron
Zhanhong Jiang
Aditya Balu
Chih-Hsuan Yang
...
Anushrut Jignasu
S. Sarkar
C. Hegde
A. Krishnamurthy
Baskar Ganapathysubramanian
AI4CE
24
7
0
07 Nov 2022
Embed and Emulate: Learning to estimate parameters of dynamical systems
  with uncertainty quantification
Embed and Emulate: Learning to estimate parameters of dynamical systems with uncertainty quantification
Ruoxi Jiang
Rebecca Willett
25
6
0
03 Nov 2022
Combined space-time reduced-order model with 3D deep convolution for
  extrapolating fluid dynamics
Combined space-time reduced-order model with 3D deep convolution for extrapolating fluid dynamics
Indu Kant Deo
Rui Gao
R. Jaiman
AI4CE
22
0
0
01 Nov 2022
Neuro-symbolic partial differential equation solver
Neuro-symbolic partial differential equation solver
Pouria A. Mistani
Samira Pakravan
Rajesh Ilango
S. Choudhry
Frédéric Gibou
31
1
0
25 Oct 2022
JAX-DIPS: Neural bootstrapping of finite discretization methods and
  application to elliptic problems with discontinuities
JAX-DIPS: Neural bootstrapping of finite discretization methods and application to elliptic problems with discontinuities
Pouria A. Mistani
Samira Pakravan
Rajesh Ilango
Frédéric Gibou
16
8
0
25 Oct 2022
SeismicNet: Physics-informed neural networks for seismic wave modeling
  in semi-infinite domain
SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain
Pu Ren
Chengping Rao
Su Chen
Jian-Xun Wang
Hao Sun
Yang Liu
44
41
0
25 Oct 2022
Less Emphasis on Difficult Layer Regions: Curriculum Learning for
  Singularly Perturbed Convection-Diffusion-Reaction Problems
Less Emphasis on Difficult Layer Regions: Curriculum Learning for Singularly Perturbed Convection-Diffusion-Reaction Problems
Yufeng Wang
Cong Xu
Min Yang
Jin Zhang
11
4
0
23 Oct 2022
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed
  Neural Networks
Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks
Shibo Li
Michael Penwarden
Yiming Xu
Conor Tillinghast
Akil Narayan
Robert M. Kirby
Shandian Zhe
AI4CE
18
4
0
23 Oct 2022
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural
  Networks on Coupled Ordinary Differential Equations
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations
Alexander New
B. Eng
A. Timm
A. Gearhart
20
4
0
14 Oct 2022
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning
PDEBENCH: An Extensive Benchmark for Scientific Machine Learning
M. Takamoto
T. Praditia
Raphael Leiteritz
Dan MacKinlay
Francesco Alesiani
Dirk Pflüger
Mathias Niepert
AI4CE
30
209
0
13 Oct 2022
A Unified Hard-Constraint Framework for Solving Geometrically Complex
  PDEs
A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs
Songming Liu
Zhongkai Hao
Chengyang Ying
Hang Su
Jun Zhu
Ze Cheng
AI4CE
18
17
0
06 Oct 2022
Homotopy-based training of NeuralODEs for accurate dynamics discovery
Homotopy-based training of NeuralODEs for accurate dynamics discovery
Joon-Hyuk Ko
Hankyul Koh
Nojun Park
W. Jhe
46
8
0
04 Oct 2022
Random Weight Factorization Improves the Training of Continuous Neural
  Representations
Random Weight Factorization Improves the Training of Continuous Neural Representations
Sizhuang He
Hanwen Wang
Jacob H. Seidman
P. Perdikaris
26
10
0
03 Oct 2022
Failure-informed adaptive sampling for PINNs
Failure-informed adaptive sampling for PINNs
Zhiwei Gao
Liang Yan
Tao Zhou
18
77
0
01 Oct 2022
Implicit Neural Spatial Representations for Time-dependent PDEs
Implicit Neural Spatial Representations for Time-dependent PDEs
Honglin Chen
Rundi Wu
E. Grinspun
Changxi Zheng
Julius Berner
AI4CE
25
33
0
30 Sep 2022
Variationally Mimetic Operator Networks
Variationally Mimetic Operator Networks
Dhruv V. Patel
Deep Ray
M. Abdelmalik
T. Hughes
Assad A. Oberai
55
23
0
26 Sep 2022
Deep Reinforcement Learning for Adaptive Mesh Refinement
Deep Reinforcement Learning for Adaptive Mesh Refinement
C. Foucart
A. Charous
Pierre FJ Lermusiaux
AI4CE
41
22
0
25 Sep 2022
A novel corrective-source term approach to modeling unknown physics in
  aluminum extraction process
A novel corrective-source term approach to modeling unknown physics in aluminum extraction process
Haakon Robinson
E. Lundby
Adil Rasheed
J. Gravdahl
20
5
0
22 Sep 2022
Approximating the full-field temperature evolution in 3D electronic
  systems from randomized "Minecraft" systems
Approximating the full-field temperature evolution in 3D electronic systems from randomized "Minecraft" systems
Monika Stipsitz
H. Sanchis-Alepuz
AI4CE
21
2
0
21 Sep 2022
Investigating and Mitigating Failure Modes in Physics-informed Neural
  Networks (PINNs)
Investigating and Mitigating Failure Modes in Physics-informed Neural Networks (PINNs)
S. Basir
PINN
AI4CE
31
21
0
20 Sep 2022
Residual-Quantile Adjustment for Adaptive Training of Physics-informed
  Neural Network
Residual-Quantile Adjustment for Adaptive Training of Physics-informed Neural Network
Jiayue Han
Zhiqiang Cai
Zhiyou Wu
Xiang Zhou
44
7
0
09 Sep 2022
Solving Elliptic Problems with Singular Sources using Singularity
  Splitting Deep Ritz Method
Solving Elliptic Problems with Singular Sources using Singularity Splitting Deep Ritz Method
Tianhao Hu
Bangti Jin
Zhi Zhou
31
6
0
07 Sep 2022
NeuralSI: Structural Parameter Identification in Nonlinear Dynamical
  Systems
NeuralSI: Structural Parameter Identification in Nonlinear Dynamical Systems
Xuyang Li
H. Bolandi
Talal Salem
N. Lajnef
Vishnu Naresh Boddeti
19
2
0
26 Aug 2022
Domain-aware Control-oriented Neural Models for Autonomous Underwater
  Vehicles
Domain-aware Control-oriented Neural Models for Autonomous Underwater Vehicles
Wenceslao Shaw-Cortez
Soumya Vasisht
Aaron Tuor
Ján Drgoňa
D. Vrabie
AI4CE
15
0
0
15 Aug 2022
PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE
  Solvers
PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers
Namgyu Kang
Byeonghyeon Lee
Youngjoon Hong
S. Yun
Eunbyung Park
PINN
AI4CE
22
13
0
26 Jul 2022
Thermodynamics of learning physical phenomena
Thermodynamics of learning physical phenomena
Elías Cueto
Francisco Chinesta
AI4CE
25
22
0
26 Jul 2022
A comprehensive study of non-adaptive and residual-based adaptive
  sampling for physics-informed neural networks
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks
Chen-Chun Wu
Min Zhu
Qinyan Tan
Yadhu Kartha
Lu Lu
32
352
0
21 Jul 2022
Learning differentiable solvers for systems with hard constraints
Learning differentiable solvers for systems with hard constraints
Geoffrey Negiar
Michael W. Mahoney
Aditi S. Krishnapriyan
31
28
0
18 Jul 2022
Earthformer: Exploring Space-Time Transformers for Earth System
  Forecasting
Earthformer: Exploring Space-Time Transformers for Earth System Forecasting
Zhihan Gao
Xingjian Shi
Hao Wang
Yi Zhu
Yuyang Wang
Mu Li
Dit-Yan Yeung
AI4TS
39
149
0
12 Jul 2022
Adaptive Self-supervision Algorithms for Physics-informed Neural
  Networks
Adaptive Self-supervision Algorithms for Physics-informed Neural Networks
Shashank Subramanian
Robert M. Kirby
Michael W. Mahoney
A. Gholami
30
25
0
08 Jul 2022
Mitigating Propagation Failures in Physics-informed Neural Networks
  using Retain-Resample-Release (R3) Sampling
Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling
Arka Daw
Jie Bu
Sizhuang He
P. Perdikaris
Anuj Karpatne
AI4CE
21
45
0
05 Jul 2022
Evaluating Error Bound for Physics-Informed Neural Networks on Linear
  Dynamical Systems
Evaluating Error Bound for Physics-Informed Neural Networks on Linear Dynamical Systems
Shuheng Liu
Xiyue Huang
P. Protopapas
PINN
24
5
0
03 Jul 2022
Momentum Diminishes the Effect of Spectral Bias in Physics-Informed
  Neural Networks
Momentum Diminishes the Effect of Spectral Bias in Physics-Informed Neural Networks
G. Farhani
Alexander Kazachek
Boyu Wang
21
6
0
29 Jun 2022
Deep Random Vortex Method for Simulation and Inference of Navier-Stokes
  Equations
Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations
Rui Zhang
Peiyan Hu
Qi Meng
Yue Wang
Rongchan Zhu
Bingguang Chen
Zhi-Ming Ma
Tie-Yan Liu
12
13
0
20 Jun 2022
Characterizing and Mitigating the Difficulty in Training
  Physics-informed Artificial Neural Networks under Pointwise Constraints
Characterizing and Mitigating the Difficulty in Training Physics-informed Artificial Neural Networks under Pointwise Constraints
S. Basir
Inanc Senocak
AI4CE
27
1
0
19 Jun 2022
Explaining the physics of transfer learning a data-driven subgrid-scale
  closure to a different turbulent flow
Explaining the physics of transfer learning a data-driven subgrid-scale closure to a different turbulent flow
Adam Subel
Yifei Guan
A. Chattopadhyay
P. Hassanzadeh
AI4CE
32
41
0
07 Jun 2022
Is $L^2$ Physics-Informed Loss Always Suitable for Training
  Physics-Informed Neural Network?
Is L2L^2L2 Physics-Informed Loss Always Suitable for Training Physics-Informed Neural Network?
Chuwei Wang
Shanda Li
Di He
Liwei Wang
AI4CE
PINN
31
28
0
04 Jun 2022
Physical Activation Functions (PAFs): An Approach for More Efficient
  Induction of Physics into Physics-Informed Neural Networks (PINNs)
Physical Activation Functions (PAFs): An Approach for More Efficient Induction of Physics into Physics-Informed Neural Networks (PINNs)
J. Abbasi
Paal Ostebo Andersen
PINN
AI4CE
25
14
0
29 May 2022
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming
Sen Na
Michael W. Mahoney
34
7
0
27 May 2022
Transformer for Partial Differential Equations' Operator Learning
Transformer for Partial Differential Equations' Operator Learning
Zijie Li
Kazem Meidani
A. Farimani
42
140
0
26 May 2022
Accelerated Training of Physics-Informed Neural Networks (PINNs) using
  Meshless Discretizations
Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations
Ramansh Sharma
Varun Shankar
37
40
0
19 May 2022
Finite Element Method-enhanced Neural Network for Forward and Inverse
  Problems
Finite Element Method-enhanced Neural Network for Forward and Inverse Problems
R. Meethal
B. Obst
Mohamed Khalil
A. Ghantasala
A. Kodakkal
K. Bletzinger
R. Wüchner
AI4CE
23
29
0
17 May 2022
Loss Landscape Engineering via Data Regulation on PINNs
Loss Landscape Engineering via Data Regulation on PINNs
Vignesh Gopakumar
Stanislas Pamela
D. Samaddar
PINN
38
16
0
16 May 2022
AutoKE: An automatic knowledge embedding framework for scientific
  machine learning
AutoKE: An automatic knowledge embedding framework for scientific machine learning
Mengge Du
Yuntian Chen
Dongxiao Zhang
AI4CE
33
11
0
11 May 2022
Physics-informed neural networks for PDE-constrained optimization and
  control
Physics-informed neural networks for PDE-constrained optimization and control
Jostein Barry-Straume
A. Sarshar
Andrey A. Popov
Adrian Sandu
PINN
AI4CE
29
14
0
06 May 2022
Lagrangian PINNs: A causality-conforming solution to failure modes of
  physics-informed neural networks
Lagrangian PINNs: A causality-conforming solution to failure modes of physics-informed neural networks
R. Mojgani
Maciej Balajewicz
P. Hassanzadeh
PINN
33
45
0
05 May 2022
Learning Green's functions associated with time-dependent partial
  differential equations
Learning Green's functions associated with time-dependent partial differential equations
N. Boullé
Seick Kim
Tianyi Shi
Alex Townsend
AI4CE
26
25
0
27 Apr 2022
Numerical Computation of Partial Differential Equations by Hidden-Layer
  Concatenated Extreme Learning Machine
Numerical Computation of Partial Differential Equations by Hidden-Layer Concatenated Extreme Learning Machine
Naxian Ni
S. Dong
29
20
0
24 Apr 2022
Competitive Physics Informed Networks
Competitive Physics Informed Networks
Qi Zeng
Yash Kothari
Spencer H. Bryngelson
F. Schafer
PINN
19
20
0
23 Apr 2022
Improved Training of Physics-Informed Neural Networks with Model
  Ensembles
Improved Training of Physics-Informed Neural Networks with Model Ensembles
Katsiaryna Haitsiukevich
Alexander Ilin
PINN
36
23
0
11 Apr 2022
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