Stiff Transfer Learning for Physics-Informed Neural Networks

Emilien Seiler, Wanzhou Lei, Pavlos Protopapas

Stiff differential equations are prevalent in various scientific domains, posing significant challenges due to the disparate time scales of their components. As computational power…