Asymptotics of representation learning in finite Bayesian neural networks*
Asymptotics of representation learning in finite Bayesian neural networks*
Abstract Recent works have suggested that finite Bayesian neural networks may sometimes outperform their infinite cousins because finite networks can flexibly adapt their internal representations. However, our theoretical understanding of how the learned hidden layer representations of finite networks differ from the fixed representations of infinite networks remains incomplete. Perturbative …