3 papers
cs.LG2026
Gradient Flow Through Diagram Expansions: Learning Regimes and Explicit Solutions
Dmitry Yarotsky, Eugene Golikov, Yaroslav Gusev
We develop a general mathematical framework to analyze scaling regimes and derive explicit analytic solutions for gradient flow (GF) in large learning problems. Our key innovation…
cs.LG2026
A prism hierarchy of learning regimes in large linear autoencoders
Eugene Golikov, Yaroslav Gusev, Dmitry Yarotsky
Theoretical studies of machine learning models commonly consider different limiting regimes in which the learning dynamics of gradient descent becomes theoretically tractable. It i…
physics.chem-ph2025
Molecular Learning Dynamics
Yaroslav Gusev, Vitaly Vanchurin
We apply the physics-learning duality to molecular systems by complementing the physical description of interacting particles with a dual learning description, where each particle…