A comparison of PINN approaches for drift-diffusion equations on metric graphs

15 May 2022

Papers citing "A comparison of PINN approaches for drift-diffusion equations on metric graphs"

9 / 9 papers shown

Title
Physics informed deep learning for computational elastodynamics without labeled data Chengping Rao Hao Sun Yang Liu PINN AI4CE 64 225 0 10 Jun 2020
A deep learning framework for solution and discovery in solid mechanics E. Haghighat M. Raissi A. Moure H. Gómez R. Juanes AI4CE PINN 76 57 0 14 Feb 2020
Physics-Informed Neural Networks for Power Systems George S. Misyris Andreas Venzke Spyros Chatzivasileiadis PINN AI4CE 67 219 0 09 Nov 2019
Constraint-Aware Neural Networks for Riemann Problems Jim Magiera Deep Ray J. Hesthaven C. Rohde AI4CE PINN 47 60 0 29 Apr 2019
Deep learning observables in computational fluid dynamics K. Lye Siddhartha Mishra Deep Ray OOD AI4CE 108 159 0 07 Mar 2019
Physics-Constrained Deep Learning for High-dimensional Surrogate Modeling and Uncertainty Quantification without Labeled Data Yinhao Zhu N. Zabaras P. Koutsourelakis P. Perdikaris PINN AI4CE 108 867 0 18 Jan 2019
Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations Siyu Dai Shawn Schaffert Andreas G. Hofmann 125 365 0 05 Nov 2018
Hidden Fluid Mechanics: A Navier-Stokes Informed Deep Learning Framework for Assimilating Flow Visualization Data M. Raissi A. Yazdani George Karniadakis AI4CE PINN 83 160 0 13 Aug 2018
Machine Learning of Linear Differential Equations using Gaussian Processes M. Raissi George Karniadakis 83 551 0 10 Jan 2017