Physics-informed neural networks with non-differentiable loss

• Main Author: Yang, Junyan
• Other Authors: Mao Kezhi
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2022
• Subjects: Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/158021
• Institution: Nanyang Technological University

Physics-informed Neural Networks (PINN) are special neural networks that are designed for scientific computing tasks. Recent research has found its promising capability to integrate any given law of physics in different forms including general nonlinear partial differentiable equations. It has sh...