Rethinking Function-Space Variational Inference in Bayesian Neural Networks

2020

Citations in the corpus

• Continual Learning via Sequential Function-Space Variational Inference (2023, methodology): “…D = ( X , y ) , a prior p ( f ) and a variational family Q f , function-space variational inference (Burt et al., 2021; Matthews et al., 2016; Rudner et al., 2021; Sun et al., 2019) consists of finding the variational distribution q ( f ) ∈ Q f that maximizes This variational optimization…”