D3M: A deep domain decomposition method for partial differential equations

24 September 2019

Papers citing "D3M: A deep domain decomposition method for partial differential equations"

42 / 42 papers shown

Title
Operator Learning with Domain Decomposition for Geometry Generalization in PDE Solving Jianing Huang Kaixuan Zhang Youjia Wu Ze Cheng AI4CE 45 0 0 01 Apr 2025
The role of interface boundary conditions and sampling strategies for Schwarz-based coupling of projection-based reduced order models Christopher Wentland Francesco Rizzi Joshua Barnett Irina Tezaur 16 3 0 07 Oct 2024
Non-overlapping, Schwarz-type Domain Decomposition Method for Physics and Equality Constrained Artificial Neural Networks Qifeng Hu S. Basir Inanc Senocak 25 0 0 20 Sep 2024
Two-level deep domain decomposition method V. Dolean Serge Gratton Alexander Heinlein Valentin Mercier AI4CE 19 0 0 22 Aug 2024
Adaptive deep density approximation for stochastic dynamical systems Junjie He Qifeng Liao Xiaoliang Wan 27 2 0 05 May 2024
Multi-Level GNN Preconditioner for Solving Large Scale Problems Matthieu Nastorg J. Gratien T. Faney M. Bucci Guillaume Charpiat Marc Schoenauer AI4CE 19 1 0 13 Feb 2024
Challenges in Training PINNs: A Loss Landscape Perspective Pratik Rathore Weimu Lei Zachary Frangella Lu Lu Madeleine Udell AI4CE PINN ODL 15 39 0 02 Feb 2024
Machine learning and domain decomposition methods -- a survey A. Klawonn M. Lanser J. Weber AI4CE 11 7 0 21 Dec 2023
Domain decomposition-based coupling of physics-informed neural networks via the Schwarz alternating method Will Snyder Irina Tezaur Christopher Wentland 11 4 0 01 Nov 2023
TSONN: Time-stepping-oriented neural network for solving partial differential equations W. Cao Weiwei Zhang AI4TS 11 1 0 25 Oct 2023
An Extreme Learning Machine-Based Method for Computational PDEs in Higher Dimensions Yiran Wang Suchuan Dong 20 35 0 13 Sep 2023
Breaking Boundaries: Distributed Domain Decomposition with Scalable Physics-Informed Neural PDE Solvers Arthur Feeney Zitong Li Ramin Bostanabad Aparna Chandramowlishwaran AI4CE 6 1 0 28 Aug 2023
A Generalized Schwarz-type Non-overlapping Domain Decomposition Method using Physics-constrained Neural Networks S. Basir Inanc Senocak AI4CE 14 3 0 23 Jul 2023
Enhancing training of physics-informed neural networks using domain-decomposition based preconditioning strategies Alena Kopanicáková Hardik Kothari George Karniadakis Rolf Krause AI4CE 8 18 0 30 Jun 2023
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs Zhongkai Hao J. Yao Chang Su Hang Su Ziao Wang ... Zeyu Xia Yichi Zhang Songming Liu Lu Lu Jun Zhu PINN 13 29 0 15 Jun 2023
Learning from Integral Losses in Physics Informed Neural Networks Ehsan Saleh Saba Ghaffari Timothy Bretl Luke N. Olson Matthew West PINN AI4CE 14 4 0 27 May 2023
ParticleWNN: a Novel Neural Networks Framework for Solving Partial Differential Equations Yaohua Zang Gang Bao 8 4 0 21 May 2023
LSA-PINN: Linear Boundary Connectivity Loss for Solving PDEs on Complex Geometry Jian Cheng Wong P. Chiu C. Ooi M. Dao Yew-Soon Ong AI4CE PINN 11 10 0 03 Feb 2023
Dirichlet-Neumann learning algorithm for solving elliptic interface problems Qi Sun Xuejun Xu Haotian Yi 19 3 0 18 Jan 2023
A domain-decomposed VAE method for Bayesian inverse problems Zhihang Xu Yingzhi Xia Qifeng Liao 11 7 0 09 Jan 2023
SciAI4Industry -- Solving PDEs for industry-scale problems with deep learning Philipp A. Witte Russell J. Hewett K. Saurabh A. Sojoodi Ranveer Chandra AI4CE 11 2 0 23 Nov 2022
Augmented Physics-Informed Neural Networks (APINNs): A gating network-based soft domain decomposition methodology Zheyuan Hu Ameya Dilip Jagtap George Karniadakis Kenji Kawaguchi 15 75 0 16 Nov 2022
Physics-Informed Machine Learning: A Survey on Problems, Methods and Applications Zhongkai Hao Songming Liu Yichi Zhang Chengyang Ying Yao Feng Hang Su Jun Zhu PINN AI4CE 16 87 0 15 Nov 2022
A composable machine-learning approach for steady-state simulations on high-resolution grids Rishikesh Ranade C. Hill Lalit Ghule Jay Pathak AI4CE 15 7 0 11 Oct 2022
Learning Interface Conditions in Domain Decomposition Solvers Ali Taghibakhshi Nicolas Nytko Tareq Uz Zaman S. MacLachlan Luke N. Olson Matthew West AI4CE 27 11 0 19 May 2022
DAS-PINNs: A deep adaptive sampling method for solving high-dimensional partial differential equations Keju Tang Xiaoliang Wan Chao Yang 13 108 0 28 Dec 2021
A coarse space acceleration of deep-DDM Valentin Mercier Serge Gratton Pierre Boudier AI4CE 14 10 0 07 Dec 2021
On Computing the Hyperparameter of Extreme Learning Machines: Algorithm and Application to Computational PDEs, and Comparison with Classical and High-Order Finite Elements S. Dong Jielin Yang 61 51 0 27 Oct 2021
Learning in Sinusoidal Spaces with Physics-Informed Neural Networks Jian Cheng Wong C. Ooi Abhishek Gupta Yew-Soon Ong AI4CE PINN SSL 11 76 0 20 Sep 2021
Finite Basis Physics-Informed Neural Networks (FBPINNs): a scalable domain decomposition approach for solving differential equations Benjamin Moseley Andrew Markham T. Nissen‐Meyer PINN 37 206 0 16 Jul 2021
Solving PDEs on Unknown Manifolds with Machine Learning Senwei Liang Shixiao W. Jiang J. Harlim Haizhao Yang AI4CE 17 16 0 12 Jun 2021
Hybrid analysis and modeling, eclecticism, and multifidelity computing toward digital twin revolution Omer San Adil Rasheed T. Kvamsdal 29 50 0 26 Mar 2021
Adaptive deep density approximation for Fokker-Planck equations Keju Tang Xiaoliang Wan Qifeng Liao 12 37 0 20 Mar 2021
Bayesian neural networks for weak solution of PDEs with uncertainty quantification Xiaoxuan Zhang K. Garikipati AI4CE 26 11 0 13 Jan 2021
Can Transfer Neuroevolution Tractably Solve Your Differential Equations? Jian Cheng Wong Abhishek Gupta Yew-Soon Ong 18 21 0 06 Jan 2021
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 12 145 0 22 Dec 2020
Friedrichs Learning: Weak Solutions of Partial Differential Equations via Deep Learning Fan Chen J. Huang Chunmei Wang Haizhao Yang 8 30 0 15 Dec 2020
Local Extreme Learning Machines and Domain Decomposition for Solving Linear and Nonlinear Partial Differential Equations S. Dong Zongwei Li 20 111 0 04 Dec 2020
A Deep Learning Approach for Predicting Spatiotemporal Dynamics From Sparsely Observed Data Priyabrata Saha Saibal Mukhopadhyay AI4CE 8 4 0 30 Nov 2020
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization Rishikesh Ranade C. Hill Jay Pathak AI4CE 38 121 0 17 May 2020
PFNN: A Penalty-Free Neural Network Method for Solving a Class of Second-Order Boundary-Value Problems on Complex Geometries H. Sheng Chao Yang 6 113 0 14 Apr 2020
hp-VPINNs: Variational Physics-Informed Neural Networks With Domain Decomposition E. Kharazmi Zhongqiang Zhang George Karniadakis 117 503 0 11 Mar 2020