2 papers
cs.LG2025
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…
cs.LG2024
Local Methods with Adaptivity via Scaling
Savelii Chezhegov, Sergey Skorik, Nikolas Khachaturov +5
The rapid development of machine learning and deep learning has introduced increasingly complex optimization challenges that must be addressed. Indeed, training modern, advanced mo…