Mikhail Aleksandrov

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

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 unstable due to the complex landscape of the loss function. To address this issue, we reformulate PINN training as a nonconvex-…