Enhancing Stability of Physics-Informed Neural Network Training Through Saddle-Point Reformulation

Dmitry Bylinkin, Mikhail Aleksandrov, Savelii Chezhegov +1

Physics-informed neural networks (PINNs) have gained prominence in recent years and are now effectively used in a number of applications. However, their performance remains unstabl…