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Exact imposition of boundary conditions with distance functions in
  physics-informed deep neural networks
v1v2 (latest)

Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks

Computer Methods in Applied Mechanics and Engineering (CMAME), 2021
17 April 2021
N. Sukumar
Ankit Srivastava
    PINNAI4CE
ArXiv (abs)PDFHTML

Papers citing "Exact imposition of boundary conditions with distance functions in physics-informed deep neural networks"

50 / 91 papers shown
DeepPAAC: A New Deep Galerkin Method for Principal-Agent Problems
DeepPAAC: A New Deep Galerkin Method for Principal-Agent Problems
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Changgen Xie
Zimu Zhu
125
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06 Nov 2025
Physics-Informed Neural Networks for Speech Production
Physics-Informed Neural Networks for Speech Production
Kazuya Yokota
Ryosuke Harakawa
Masaaki Baba
Masahiro Iwahashi
60
0
0
01 Nov 2025
Enforcing boundary conditions for physics-informed neural operators
Enforcing boundary conditions for physics-informed neural operators
Niklas Göschel
Sebastian Götschel
Daniel Ruprecht
AI4CE
108
0
0
28 Oct 2025
A Physics-informed Multi-resolution Neural Operator
A Physics-informed Multi-resolution Neural Operator
Sumanta Roy
B. Bahmani
Ioannis G. Kevrekidis
Michael D. Shields
AI4CE
116
1
0
27 Oct 2025
Finding geodesics with the Deep Ritz method
Finding geodesics with the Deep Ritz method
Conor Rowan
AI4CE
156
0
0
16 Oct 2025
Nonlinear discretizations and Newton's method: characterizing stationary points of regression objectives
Nonlinear discretizations and Newton's method: characterizing stationary points of regression objectives
Conor Rowan
ODL
228
1
0
13 Oct 2025
A physics-aware deep learning model for shear band formation around collapsing pores in shocked reactive materials
A physics-aware deep learning model for shear band formation around collapsing pores in shocked reactive materialsJournal of Applied Physics (JAP), 2025
Xinlun Cheng
Bingzhe Chen
Joseph B. Choi
Y. Nguyen
P. Seshadri
Mayank Verma
H. Udaykumar
Stephen Seung-Yeob Baek
AI4CE
100
1
0
08 Oct 2025
BEKAN: Boundary condition-guaranteed evolutionary Kolmogorov-Arnold networks with radial basis functions for solving PDE problems
BEKAN: Boundary condition-guaranteed evolutionary Kolmogorov-Arnold networks with radial basis functions for solving PDE problems
Bongseok Kim
Jiahao Zhang
Guang Lin
96
0
0
03 Oct 2025
Multi-patch isogeometric neural solver for partial differential equations on computer-aided design domains
Multi-patch isogeometric neural solver for partial differential equations on computer-aided design domains
M. V. Tresckow
Ion Gabriel Ion
Dimitrios Loukrezis
AI4CE
88
0
0
29 Sep 2025
A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning
A Variational Framework for Residual-Based Adaptivity in Neural PDE Solvers and Operator Learning
Juan Diego Toscano
Daniel T. Chen
Vivek Oommen
Jérome Darbon
George Karniadakis
169
2
0
17 Sep 2025
Physics-informed low-rank neural operators with application to parametric elliptic PDEs
Physics-informed low-rank neural operators with application to parametric elliptic PDEs
Sebastian Schaffer
Lukas Exl
AI4CE
92
0
0
09 Sep 2025
Variational volume reconstruction with the Deep Ritz Method
Variational volume reconstruction with the Deep Ritz Method
Conor Rowan
Sumedh Soman
John A. Evans
85
1
0
08 Aug 2025
SO-PIFRNN: Self-optimization physics-informed Fourier-features randomized neural network for solving partial differential equations
SO-PIFRNN: Self-optimization physics-informed Fourier-features randomized neural network for solving partial differential equations
Jiale Linghu
Weifeng Gao
Hao Dong
Yufeng Nie
104
0
0
07 Aug 2025
Solved in Unit Domain: JacobiNet for Differentiable Coordinate-Transformed PINNs
Solved in Unit Domain: JacobiNet for Differentiable Coordinate-Transformed PINNs
Xi Chen
J. Yang
Junjie Zhang
Runnan Yang
Xu Liu
Hong Wang
Tinghui Zheng
Ziyu Ren
Wenqi Hu
102
0
0
04 Aug 2025
Bayesian BiLO: Bilevel Local Operator Learning for Efficient Uncertainty Quantification of Bayesian PDE Inverse Problems with Low-Rank Adaptation
Bayesian BiLO: Bilevel Local Operator Learning for Efficient Uncertainty Quantification of Bayesian PDE Inverse Problems with Low-Rank Adaptation
Ray Zirui Zhang
Christopher E. Miles
Xiaohui Xie
John S. Lowengrub
214
0
0
22 Jul 2025
Solving engineering eigenvalue problems with neural networks using the Rayleigh quotient
Conor Rowan
John A. Evans
K. Maute
Alireza Doostan
241
4
0
04 Jun 2025
Solving Nonlinear PDEs with Sparse Radial Basis Function Networks
Solving Nonlinear PDEs with Sparse Radial Basis Function Networks
Zihan Shao
Konstantin Pieper
Xiaochuan Tian
442
3
0
12 May 2025
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force method
Physics-informed solution reconstruction in elasticity and heat transfer using the explicit constraint force methodComputer Methods in Applied Mechanics and Engineering (CMAME), 2025
Conor Rowan
K. Maute
Alireza Doostan
AI4CE
208
3
0
08 May 2025
Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models
Physics-informed neural network estimation of active material properties in time-dependent cardiac biomechanical models
Matthias Höfler
Francesco Regazzoni
S. Pagani
Elias Karabelas
Christoph M. Augustin
Gundolf Haase
Gernot Plank
Federica Caforio
175
2
0
06 May 2025
Multi-level datasets training method in Physics-Informed Neural Networks
Multi-level datasets training method in Physics-Informed Neural Networks
Yao-Hsuan Tsai
Hsiao-Tung Juan
Pao-Hsiung Chiu
Chao-An Lin
AI4CE
289
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0
30 Apr 2025
Reliable and efficient inverse analysis using physics-informed neural networks with normalized distance functions and adaptive weight tuning
Reliable and efficient inverse analysis using physics-informed neural networks with normalized distance functions and adaptive weight tuning
Shota Deguchi
Mitsuteru Asai
PINNAI4CE
502
0
0
25 Apr 2025
Hard-constraining Neumann boundary conditions in physics-informed neural networks via Fourier feature embeddings
Hard-constraining Neumann boundary conditions in physics-informed neural networks via Fourier feature embeddings
Christopher Straub
Philipp Brendel
Vlad Medvedev
A. Rosskopf
302
5
0
01 Apr 2025
Solving 2-D Helmholtz equation in the rectangular, circular, and elliptical domains using neural networks
Solving 2-D Helmholtz equation in the rectangular, circular, and elliptical domains using neural networksJournal of Sound and Vibration (JSV), 2025
D. Veerababu
Prasanta K. Ghosh
201
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0
26 Mar 2025
Physics-constrained DeepONet for Surrogate CFD models: a curved backward-facing step case
Anas Jnini
Harshinee Goordoyal
Sujal Dave
Flavio Vella
Katharine H. Fraser
Artem Korobenko
PINN
216
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14 Mar 2025
An explainable operator approximation framework under the guideline of Green's function
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Jianghang Gu
Ling Wen
Yuntian Chen
Shiyi Chen
382
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0
21 Dec 2024
Variational formulation based on duality to solve partial differential equations: Use of B-splines and machine learning approximants
Variational formulation based on duality to solve partial differential equations: Use of B-splines and machine learning approximantsComputer Methods in Applied Mechanics and Engineering (CMAME), 2024
N. Sukumar
Amit Acharya
349
4
0
02 Dec 2024
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning
The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine LearningNeural Information Processing Systems (NeurIPS), 2024
Ruben Ohana
Michael McCabe
Lucas Meyer
Rudy Morel
Fruzsina J. Agocs
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François Rozet
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M. Cranmer
S. Ho
Shirley Ho
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482
64
1
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Gaussian Process Priors for Boundary Value Problems of Linear Partial Differential Equations
Gaussian Process Priors for Boundary Value Problems of Linear Partial Differential Equations
Jianle iHuang
Marc Härkönen
Markus Lange-Hegermann
Bogdan Raiță
276
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25 Nov 2024
From PINNs to PIKANs: Recent Advances in Physics-Informed Machine
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From PINNs to PIKANs: Recent Advances in Physics-Informed Machine Learning
Juan Diego Toscano
Vivek Oommen
Alan John Varghese
Zongren Zou
Nazanin Ahmadi Daryakenari
Chenxi Wu
George Karniadakis
PINNAI4CE
218
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Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases
Madison Cooley
Varun Shankar
Robert M. Kirby
Shandian Zhe
328
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Deep Learning Alternatives of the Kolmogorov Superposition Theorem
Deep Learning Alternatives of the Kolmogorov Superposition TheoremInternational Conference on Learning Representations (ICLR), 2024
Leonardo Ferreira Guilhoto
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Physics aware machine learning for micromagnetic energy minimization:
  recent algorithmic developments
Physics aware machine learning for micromagnetic energy minimization: recent algorithmic developmentsComputer Physics Communications (CPC), 2024
Sebastian Schaffer
T. Schrefl
Harald Oezelt
Norbert J Mauser
Lukas Exl
AI4CE
263
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19 Sep 2024
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling
Alex Glyn-Davies
Arnaud Vadeboncoeur
O. Deniz Akyildiz
Ieva Kazlauskaite
Mark Girolami
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400
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10 Sep 2024
Accelerating the discovery of steady-states of planetary interior
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Accelerating the discovery of steady-states of planetary interior dynamics with machine learning
Siddhant Agarwal
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Christian Huttig
David S. Greenberg
A. Bekar
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194
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Improving PINNs By Algebraic Inclusion of Boundary and Initial
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Improving PINNs By Algebraic Inclusion of Boundary and Initial Conditions
Mohan Ren
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223
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Differentiable Neural-Integrated Meshfree Method for Forward and Inverse
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Differentiable Neural-Integrated Meshfree Method for Forward and Inverse Modeling of Finite Strain Hyperelasticity
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Extremization to Fine Tune Physics Informed Neural Networks for Solving
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Extremization to Fine Tune Physics Informed Neural Networks for Solving Boundary Value ProblemsCommunications in nonlinear science & numerical simulation (CNSNS), 2024
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Astral: training physics-informed neural networks with error majorants
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256
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Robust Biharmonic Skinning Using Geometric Fields
Robust Biharmonic Skinning Using Geometric Fields
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Unveiling the optimization process of Physics Informed Neural Networks:
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Gas Source Localization Using physics Guided Neural Networks
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BiLO: Bilevel Local Operator Learning for PDE Inverse Problems. Part I: PDE-Constrained Optimization
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467
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Learning in PINNs: Phase transition, total diffusion, and generalization
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Boundary-Aware Value Function Generation for Safe Stochastic Motion
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Physics-Guided Neural Networks for Intraventricular Vector Flow Mapping
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Exact Enforcement of Temporal Continuity in Sequential Physics-Informed
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