Showing cs.LGShow all
2 papers · 1 filter
cs.LG2026
Large Spikes in Stochastic Gradient Descent: A Large-Deviations View
Benjamin Gess, Daniel Heydecker
Large loss spikes in stochastic gradient descent are studied through a rigorous large-deviations analysis for a shallow, fully connected network in the NTK scaling. In contrast to…
cs.LG2025
THINNs: Thermodynamically Informed Neural Networks
Javier Castro, Benjamin Gess
Physics-Informed Neural Networks (PINNs) are a class of deep learning models aiming to approximate solutions of PDEs by training neural networks to minimize the residual of the equ…