PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs

23 September 2019

Papers citing "PPINN: Parareal Physics-Informed Neural Network for time-dependent PDEs"

33 / 33 papers shown

Title
Uncertainty propagation in feed-forward neural network models Jeremy Diamzon Daniele Venturi 60 0 0 27 Mar 2025
Physics-informed deep learning for infectious disease forecasting Y. Qian Éric Marty Avranil Basu Avranil Basu Eamon B. O'Dea Xianqiao Wang Spencer Fox Pejman Rohani John M. Drake He Li PINN AI4CE 80 2 0 16 Jan 2025
Nearest Neighbors GParareal: Improving Scalability of Gaussian Processes for Parallel-in-Time Solvers Guglielmo Gattiglio Lyudmila Grigoryeva M. Tamborrino 27 1 0 20 May 2024
Physics-informed Deep Learning to Solve Three-dimensional Terzaghi Consolidation Equation: Forward and Inverse Problems Biao Yuan Ana Heitor He Wang Xiaohui Chen AI4CE PINN 31 1 0 08 Jan 2024
Adversarial Training for Physics-Informed Neural Networks Yao Li Shengzhu Shi Zhichang Guo Boying Wu AAML PINN 25 0 0 18 Oct 2023
Neural tangent kernel analysis of PINN for advection-diffusion equation M. Saadat B. Gjorgiev L. Das G. Sansavini 25 0 0 21 Nov 2022
Tunable Complexity Benchmarks for Evaluating Physics-Informed Neural Networks on Coupled Ordinary Differential Equations Alexander New B. Eng A. Timm A. Gearhart 17 4 0 14 Oct 2022
Semi-analytic PINN methods for singularly perturbed boundary value problems G. Gie Youngjoon Hong Chang-Yeol Jung PINN 8 5 0 19 Aug 2022
A comprehensive study of non-adaptive and residual-based adaptive sampling for physics-informed neural networks Chen-Chun Wu M. Zhu Qinyan Tan Yadhu Kartha Lu Lu 24 351 0 21 Jul 2022
Unsupervised Legendre-Galerkin Neural Network for Singularly Perturbed Partial Differential Equations Junho Choi N. Kim Youngjoon Hong AI4CE 24 0 0 21 Jul 2022
Lagrangian PINNs: A causality-conforming solution to failure modes of physics-informed neural networks R. Mojgani Maciej Balajewicz P. Hassanzadeh PINN 25 45 0 05 May 2022
A Review of Machine Learning Methods Applied to Structural Dynamics and Vibroacoustic Barbara Z Cunha C. Droz A. Zine Stéphane Foulard M. Ichchou AI4CE 29 84 0 13 Apr 2022
$Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations$ Monte Carlo PINNs: deep learning approach for forward and inverse problems involving high dimensional fractional partial differential equations Ling Guo Hao Wu Xiao-Jun Yu Tao Zhou PINN AI4CE 21 58 0 16 Mar 2022
Physics Informed RNN-DCT Networks for Time-Dependent Partial Differential Equations Benwei Wu O. Hennigh Jan Kautz S. Choudhry Wonmin Byeon MLAU AI4CE 4 10 0 24 Feb 2022
Learning Stochastic Dynamics with Statistics-Informed Neural Network Yuanran Zhu Yunhao Tang Changho Kim 19 18 0 24 Feb 2022
GParareal: A time-parallel ODE solver using Gaussian process emulation K. Pentland M. Tamborrino Timothy John Sullivan J. Buchanan Lynton C. Appel 11 8 0 31 Jan 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 1,177 0 14 Jan 2022
A coarse space acceleration of deep-DDM Valentin Mercier Serge Gratton Pierre Boudier AI4CE 33 10 0 07 Dec 2021
An extended physics informed neural network for preliminary analysis of parametric optimal control problems N. Demo M. Strazzullo G. Rozza PINN 31 33 0 26 Oct 2021
Multi-Objective Loss Balancing for Physics-Informed Deep Learning Rafael Bischof M. Kraus PINN AI4CE 33 92 0 19 Oct 2021
A Review of Physics-based Machine Learning in Civil Engineering S. Vadyala S. N. Betgeri J. Matthews Elizabeth Matthews AI4CE 25 152 0 09 Oct 2021
PCNN: A physics-constrained neural network for multiphase flows Haoyang Zheng Ziyang Huang Guang Lin PINN 19 8 0 18 Sep 2021
Legendre Deep Neural Network (LDNN) and its application for approximation of nonlinear Volterra Fredholm Hammerstein integral equations Z. Hajimohammadi Kourosh Parand A. Ghodsi 28 4 0 27 Jun 2021
Multifidelity Modeling for Physics-Informed Neural Networks (PINNs) Michael Penwarden Shandian Zhe A. Narayan Robert M. Kirby 13 42 0 25 Jun 2021
Long-time integration of parametric evolution equations with physics-informed DeepONets Sifan Wang P. Perdikaris AI4CE 17 117 0 09 Jun 2021
Neural network architectures using min-plus algebra for solving certain high dimensional optimal control problems and Hamilton-Jacobi PDEs Jérome Darbon P. Dower Tingwei Meng 6 22 0 07 May 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 651 0 20 Mar 2021
Evolutional Deep Neural Network Yifan Du T. Zaki 16 68 0 18 Mar 2021
Performance Comparison for Scientific Computations on the Edge via Relative Performance Aravind Sankaran Paolo Bientinesi 12 4 0 25 Feb 2021
An overview on deep learning-based approximation methods for partial differential equations C. Beck Martin Hutzenthaler Arnulf Jentzen Benno Kuckuck 30 146 0 22 Dec 2020
Physics-informed Neural-Network Software for Molecular Dynamics Applications Taufeq Mohammed Razakh Beibei Wang Shane Jackson R. Kalia A. Nakano K. Nomura P. Vashishta PINN 11 11 0 06 Nov 2020
Deep learning of free boundary and Stefan problems Sifan Wang P. Perdikaris 21 80 0 04 Jun 2020
DiscretizationNet: A Machine-Learning based solver for Navier-Stokes Equations using Finite Volume Discretization Rishikesh Ranade C. Hill Jay Pathak AI4CE 46 123 0 17 May 2020