PhySRNet: Physics informed super-resolution network for application in computational solid mechanics

30 June 2022

Papers citing "PhySRNet: Physics informed super-resolution network for application in computational solid mechanics"

9 / 9 papers shown

Title
Super-Resolution works for coastal simulations Zhi-Song Liu Markus Buttner V. Aizinger Andreas Rupp SupR 30 0 0 29 Aug 2024
Redefining Super-Resolution: Fine-mesh PDE predictions without classical simulations Rajat Kumar Sarkar Ritam Majumdar Vishal Sudam Jadhav Sakhinana Sagar Srinivas Venkataramana Runkana AI4CE DiffM 24 2 0 16 Nov 2023
An Operator Learning Framework for Spatiotemporal Super-resolution of Scientific Simulations Valentin Duruisseaux Amit Chakraborty AI4CE 16 1 0 04 Nov 2023
A Deep Learning Framework for Solving Hyperbolic Partial Differential Equations: Part I Rajat Arora PINN AI4CE 22 1 0 09 Jul 2023
Physics-Informed Computer Vision: A Review and Perspectives C. Banerjee Kien Nguyen Clinton Fookes G. Karniadakis PINN AI4CE 34 29 0 29 May 2023
Spatio-Temporal Super-Resolution of Dynamical Systems using Physics-Informed Deep-Learning Rajat Arora Ankit Shrivastava AI4CE 36 4 0 08 Dec 2022
Physics-Guided, Physics-Informed, and Physics-Encoded Neural Networks in Scientific Computing Salah A. Faroughi N. Pawar C. Fernandes Maziar Raissi Subasish Das N. Kalantari S. K. Mahjour PINN AI4CE 27 49 0 14 Nov 2022
Physics-informed neural networks for modeling rate- and temperature-dependent plasticity Rajat Arora P. Kakkar Biswadip Dey Amit Chakraborty PINN AI4CE 36 19 0 20 Jan 2022
MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework C. Jiang S. Esmaeilzadeh Kamyar Azizzadenesheli K. Kashinath Mustafa A. Mustafa H. Tchelepi P. Marcus P. Prabhat Anima Anandkumar AI4CE 187 141 0 01 May 2020