2 papers
cs.LG2026
Incorruptible Neural Networks: Training Models that can Generalize to Large Internal Perturbations
Philip Jacobson, Ben Feinberg, Suhas Kumar +3
Flat regions of the neural network loss landscape have long been hypothesized to correlate with better generalization properties. A closely related but distinct problem is training…
cs.LG2025
Analog Bayesian neural networks are insensitive to the shape of the weight distribution
Ravi G. Patel, T. Patrick Xiao, Sapan Agarwal +1
Recent work has demonstrated that Bayesian neural networks (BNN's) trained with mean field variational inference (MFVI) can be implemented in analog hardware, promising orders of m…