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

17 April 2021

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

26 / 76 papers shown

Title
BINN: A deep learning approach for computational mechanics problems based on boundary integral equations Jia Sun Yinghua Liu Yizheng Wang Z. Yao Xiao-ping Zheng PINN AI4CE 22 23 0 11 Jan 2023
Harmonic (Quantum) Neural Networks Atiyo Ghosh Antonio A. Gentile M. Dagrada Chul Lee S. Kim Hyukgeun Cha Yunjun Choi Brad Kim J. Kye V. Elfving AI4CE 40 1 0 14 Dec 2022
Utilising physics-guided deep learning to overcome data scarcity Jinshuai Bai Laith Alzubaidi Qingxia Wang E. Kuhl Bennamoun Yuantong T. Gu PINN AI4CE 39 3 0 24 Nov 2022
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
$Adaptive deep density approximation for fractional Fokker-Planck equations$ Adaptive deep density approximation for fractional Fokker-Planck equations Li Zeng Xiaoliang Wan Tao Zhou 21 5 0 26 Oct 2022
FO-PINNs: A First-Order formulation for Physics Informed Neural Networks R. J. Gladstone M. A. Nabian N. Sukumar Ankit Srivastava Hadi Meidani PINN AI4CE 23 0 0 25 Oct 2022
Physics-Informed Neural Networks for Shell Structures Jan-Hendrik Bastek D. Kochmann AI4CE 18 51 0 26 Jul 2022
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
Anisotropic, Sparse and Interpretable Physics-Informed Neural Networks for PDEs A. A. Ramabathiran P. Ramachandran AI4CE 19 0 0 01 Jul 2022
Deep learning approximations for non-local nonlinear PDEs with Neumann boundary conditions V. Boussange S. Becker Arnulf Jentzen Benno Kuckuck Loïc Pellissier 25 12 0 07 May 2022
Enhanced Physics-Informed Neural Networks with Augmented Lagrangian Relaxation Method (AL-PINNs) Hwijae Son S. Cho H. Hwang PINN 25 41 0 29 Apr 2022
Improved Training of Physics-Informed Neural Networks with Model Ensembles Katsiaryna Haitsiukevich Alexander Ilin PINN 39 23 0 11 Apr 2022
Calibrating constitutive models with full-field data via physics informed neural networks Craig M. Hamel K. Long S. Kramer AI4CE 27 28 0 30 Mar 2022
Respecting causality is all you need for training physics-informed neural networks Sizhuang He Shyam Sankaran P. Perdikaris PINN CML AI4CE 49 199 0 14 Mar 2022
Gradient-enhanced physics-informed neural networks for forward and inverse PDE problems Jeremy Yu Lu Lu Xuhui Meng George Karniadakis PINN AI4CE 38 451 0 01 Nov 2021
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs Biswajit Khara Aditya Balu Ameya Joshi S. Sarkar C. Hegde A. Krishnamurthy Baskar Ganapathysubramanian 39 19 0 04 Oct 2021
CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries Yi-Zhou Wang Jia Sun Wei Li Zaiyuan Lu Yinghua Liu 47 37 0 25 Sep 2021
Physics-informed neural networks for one-dimensional sound field predictions with parameterized sources and impedance boundaries N. Borrel-Jensen A. Engsig-Karup C. Jeong AI4CE 20 34 0 23 Sep 2021
Variational Physics Informed Neural Networks: the role of quadratures and test functions S. Berrone C. Canuto Moreno Pintore 31 41 0 05 Sep 2021
Training multi-objective/multi-task collocation physics-informed neural network with student/teachers transfer learnings B. Bahmani WaiChing Sun PINN AI4CE 36 17 0 24 Jul 2021
Mosaic Flows: A Transferable Deep Learning Framework for Solving PDEs on Unseen Domains Hengjie Wang R. Planas Aparna Chandramowlishwaran Ramin Bostanabad AI4CE 50 61 0 22 Apr 2021
SPINN: Sparse, Physics-based, and partially Interpretable Neural Networks for PDEs A. A. Ramabathiran P. Ramachandran PINN AI4CE 27 76 0 25 Feb 2021
On the eigenvector bias of Fourier feature networks: From regression to solving multi-scale PDEs with physics-informed neural networks Sizhuang He Hanwen Wang P. Perdikaris 131 439 0 18 Dec 2020
$NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework$ NVIDIA SimNet^{TM}: an AI-accelerated multi-physics simulation framework O. Hennigh S. Narasimhan M. A. Nabian Akshay Subramaniam Kaustubh Tangsali M. Rietmann J. Ferrandis Wonmin Byeon Z. Fang S. Choudhry PINN AI4CE 93 126 0 14 Dec 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 128 509 0 11 Mar 2020
An Energy Approach to the Solution of Partial Differential Equations in Computational Mechanics via Machine Learning: Concepts, Implementation and Applications E. Samaniego C. Anitescu S. Goswami Vien Minh Nguyen-Thanh Hongwei Guo Khader M. Hamdia Timon Rabczuk X. Zhuang PINN AI4CE 159 1,342 0 27 Aug 2019