Physics-informed neural networks with hard constraints for inverse design

9 February 2021

Papers citing "Physics-informed neural networks with hard constraints for inverse design"

50 / 60 papers shown

Title
Good Things Come in Pairs: Paired Autoencoders for Inverse Problems Matthias Chung Bas Peters Michael Solomon 34 0 0 10 May 2025
Is the end of Insight in Sight ? J. Tucny M. Durve S. Succi 59 0 0 07 May 2025
Reliable and Efficient Inverse Analysis using Physics-Informed Neural Networks with Distance Functions and Adaptive Weight Tuning Shota Deguchi Mitsuteru Asai PINN AI4CE 81 0 0 25 Apr 2025
A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction Leander Kurscheidt Paolo Morettin Roberto Sebastiani Andrea Passerini Antonio Vergari 57 0 0 25 Mar 2025
Implicit Bias in Matrix Factorization and its Explicit Realization in a New Architecture Yikun Hou Suvrit Sra A. Yurtsever 34 0 0 28 Jan 2025
Neural Port-Hamiltonian Differential Algebraic Equations for Compositional Learning of Electrical Networks Cyrus Neary Nathan Tsao Ufuk Topcu 77 1 0 15 Dec 2024
Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators Zekun Shi Zheyuan Hu Min-Bin Lin Kenji Kawaguchi 145 5 0 27 Nov 2024
Fourier PINNs: From Strong Boundary Conditions to Adaptive Fourier Bases Madison Cooley Varun Shankar Robert M. Kirby Shandian Zhe 32 2 0 04 Oct 2024
Improved physics-informed neural network in mitigating gradient related failures Pancheng Niu Yongming Chen Jun Guo Yuqian Zhou Minfu Feng Yanchao Shi PINN AI4CE 26 0 0 28 Jul 2024
Robust Biharmonic Skinning Using Geometric Fields Ana Dodik Vincent Sitzmann Justin Solomon Oded Stein 3DH 42 2 0 01 Jun 2024
Unveiling the optimization process of Physics Informed Neural Networks: How accurate and competitive can PINNs be? Jorge F. Urbán P. Stefanou José A. Pons PINN 45 6 0 07 May 2024
BiLO: Bilevel Local Operator Learning for PDE inverse problems Ray Zirui Zhang Xiaohui Xie John S. Lowengrub 68 1 0 27 Apr 2024
Neural Parameter Regression for Explicit Representations of PDE Solution Operators Konrad Mundinger Max Zimmer Sebastian Pokutta 50 0 0 19 Mar 2024
Learning solution operators of PDEs defined on varying domains via MIONet Shanshan Xiao Pengzhan Jin Yifa Tang 50 3 0 23 Feb 2024
Data-Driven Physics-Informed Neural Networks: A Digital Twin Perspective Sunwoong Yang Hojin Kim Y. Hong K. Yee R. Maulik Namwoo Kang PINN AI4CE 31 17 0 05 Jan 2024
Dynamically configured physics-informed neural network in topology optimization applications Ji-Cheng Yin Ziming Wen Shuhao Li Yaya Zhang Hu Wang AI4CE PINN 44 4 0 12 Dec 2023
Physics-informed neural networks for transformed geometries and manifolds Samuel Burbulla AI4CE 27 0 0 27 Nov 2023
Exact and soft boundary conditions in Physics-Informed Neural Networks for the Variable Coefficient Poisson equation Sebastian Barschkis 26 1 0 04 Oct 2023
Physics-Informed Neural Networks for an optimal counterdiabatic quantum computation Antonio Ferrer-Sánchez Carlos Flores-Garrigós C. Hernani-Morales José J. Orquín-Marqués N. N. Hegade Alejandro Gomez Cadavid Iraitz Montalban Enrique Solano Yolanda Vives-Gilabert J. D. Martín-Guerrero 32 2 0 08 Sep 2023
Learning Specialized Activation Functions for Physics-informed Neural Networks Honghui Wang Lu Lu Shiji Song Gao Huang PINN AI4CE 16 11 0 08 Aug 2023
Residual-based attention and connection to information bottleneck theory in PINNs Sokratis J. Anagnostopoulos Juan Diego Toscano Nikos Stergiopulos George Karniadakis 25 20 0 01 Jul 2023
Pseudo-Hamiltonian neural networks for learning partial differential equations Sølve Eidnes K. Lye 26 10 0 27 Apr 2023
A physics-informed neural network framework for modeling obstacle-related equations Hamid EL Bahja J. C. Hauffen P. Jung B. Bah Issa Karambal PINN AI4CE 29 3 0 07 Apr 2023
NSGA-PINN: A Multi-Objective Optimization Method for Physics-Informed Neural Network Training B.-L. Lu Christian Moya Guang Lin PINN 37 11 0 03 Mar 2023
Error convergence and engineering-guided hyperparameter search of PINNs: towards optimized I-FENN performance Panos Pantidis Habiba Eldababy Christopher Miguel Tagle M. Mobasher 35 20 0 03 Mar 2023
Experimental observation on a low-rank tensor model for eigenvalue problems Jun Hu Pengzhan Jin 11 2 0 01 Feb 2023
Estimation of fibre architecture and scar in myocardial tissue using electrograms: an in-silico study Konstantinos Ntagiantas E. Pignatelli N. Peters C. Cantwell R. Chowdhury Anil A. Bharath 21 1 0 06 Dec 2022
Neural DAEs: Constrained neural networks Tue Boesen E. Haber Uri M. Ascher 39 3 0 25 Nov 2022
Physics-Informed Koopman Network Yuying Liu A. Sholokhov Hassan Mansour S. Nabi AI4CE 31 3 0 17 Nov 2022
Physics-informed neural networks for operator equations with stochastic data Paul Escapil-Inchauspé G. A. Ruz 34 2 0 15 Nov 2022
Partial Differential Equations Meet Deep Neural Networks: A Survey Shudong Huang Wentao Feng Chenwei Tang Jiancheng Lv AI4CE AIMat 26 17 0 27 Oct 2022
A Dimension-Augmented Physics-Informed Neural Network (DaPINN) with High Level Accuracy and Efficiency Weilong Guan Kai-Ping Yang Yinsheng Chen Zhong Guan PINN AI4CE 18 12 0 19 Oct 2022
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
A Model-Constrained Tangent Slope Learning Approach for Dynamical Systems Hai V. Nguyen T. Bui-Thanh 36 2 0 09 Aug 2022
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 Geoffrey Negiar Michael W. Mahoney Aditi S. Krishnapriyan 31 28 0 18 Jul 2022
TT-PINN: A Tensor-Compressed Neural PDE Solver for Edge Computing Z. Liu Xinling Yu Zheng-Wei Zhang PINN 13 7 0 04 Jul 2022
Hybrid thermal modeling of additive manufacturing processes using physics-informed neural networks for temperature prediction and parameter identification Shuheng Liao Tianju Xue Jihoon Jeong Samantha Webster K. Ehmann Jian Cao AI4CE 30 46 0 15 Jun 2022
Statistical Inference of Constrained Stochastic Optimization via Sketched Sequential Quadratic Programming Sen Na Michael W. Mahoney 34 7 0 27 May 2022
Scalable algorithms for physics-informed neural and graph networks K. Shukla Mengjia Xu N. Trask George Karniadakis PINN AI4CE 72 40 0 16 May 2022
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 R. Mojgani Maciej Balajewicz P. Hassanzadeh PINN 33 45 0 05 May 2022
Improved Training of Physics-Informed Neural Networks with Model Ensembles Katsiaryna Haitsiukevich Alexander Ilin PINN 36 23 0 11 Apr 2022
Sliced gradient-enhanced Kriging for high-dimensional function approximation Kai Cheng Ralf Zimmermann 26 7 0 05 Apr 2022
On the Role of Fixed Points of Dynamical Systems in Training Physics-Informed Neural Networks Franz M. Rohrhofer S. Posch C. Gößnitzer Bernhard C. Geiger PINN 36 17 0 25 Mar 2022
Respecting causality is all you need for training physics-informed neural networks Sizhuang He Shyam Sankaran P. Perdikaris PINN CML AI4CE 46 199 0 14 Mar 2022
WaveY-Net: Physics-augmented deep learning for high-speed electromagnetic simulation and optimization Ming-Keh Chen Robert Lupoiu Chenkai Mao Der-Han Huang Jiaqi Jiang P. Lalanne Jonathan A. Fan 28 19 0 02 Mar 2022
MIONet: Learning multiple-input operators via tensor product Pengzhan Jin Shuai Meng Lu Lu 20 158 0 12 Feb 2022
Scientific Machine Learning through Physics-Informed Neural Networks: Where we are and What's next S. Cuomo Vincenzo Schiano Di Cola F. Giampaolo G. Rozza Maizar Raissi F. Piccialli PINN 26 1,180 0 14 Jan 2022
Physics-enhanced deep surrogates for partial differential equations R. Pestourie Youssef Mroueh Chris Rackauckas Payel Das Steven G. Johnson PINN AI4CE 25 15 0 10 Nov 2021