arXiv stat.ML
· Papers
Width-Robust Learnability in Mean-Field Bayesian Neural Networks
arXiv:2607.05735v1 Announce Type: new Abstract: Infinite-width limits are a standard way to reason about neural networks, but it is not automatic that the limiting learner has the same complexity-theoretic inductive bias as large finite networks. We study this question for Bayesian neural networks at the mean-field, or