Parameter Identification for Partial Differential Equations with Spatiotemporal Varying Coefficients

30 June 2023

Papers citing "Parameter Identification for Partial Differential Equations with Spatiotemporal Varying Coefficients"

9 / 9 papers shown

Title
Respecting causality is all you need for training physics-informed neural networks Sizhuang He Shyam Sankaran P. Perdikaris PINN CML AI4CE 143 203 0 14 Mar 2022
Physics-informed neural networks for inverse problems in supersonic flows Ameya Dilip Jagtap Zhiping Mao Nikolaus Adams George Karniadakis PINN 43 221 0 23 Feb 2022
Physics-informed neural networks with hard constraints for inverse design Lu Lu R. Pestourie Wenjie Yao Zhicheng Wang F. Verdugo Steven G. Johnson PINN 97 520 0 09 Feb 2021
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism L. McClenny U. Braga-Neto PINN 84 459 0 07 Sep 2020
Solving Allen-Cahn and Cahn-Hilliard Equations using the Adaptive Physics Informed Neural Networks Colby Wight Jia Zhao 77 225 0 09 Jul 2020
Physics-informed Neural Networks for Solving Inverse Problems of Nonlinear Biot's Equations: Batch Training T. Kadeethum T. Jørgensen H. Nick PINN AI4CE 132 20 0 18 May 2020
Novel semi-metrics for multivariate change point analysis and anomaly detection Nick James Max Menzies Lamiae Azizi J. Chan 34 28 0 04 Nov 2019
Physics Informed Deep Learning (Part II): Data-driven Discovery of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 91 614 0 28 Nov 2017
Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations M. Raissi P. Perdikaris George Karniadakis PINN AI4CE 82 931 0 28 Nov 2017