Data vs. Physics: The Apparent Pareto Front of Physics-Informed Neural Networks

Physics-informed neural networks (PINNs) have emerged as a promising deep learning method, capable of solving forward and inverse problems governed by differential equations. Despite their recent advance, it is widely acknowledged that PINNs are difficult to train and often require a careful tuning...

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Bibliographic Details

Published in:	IEEE Access
Main Authors:	Franz M. Rohrhofer, Stefan Posch, Clemens Gobnitzer, Bernhard C. Geiger
Format:	Article
Language:	English
Published:	IEEE 2023-01-01
Subjects:	Multi-objective optimization Pareto front physics-informed neural networks system parameters
Online Access:	https://ieeexplore.ieee.org/document/10210413/