5 citations · 5 across the 2 of their papers we have counts for
2 papers
stat.ML2022
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks
Jiayu Yao, Yaniv Yacoby, Beau Coker +2
Comparing Bayesian neural networks (BNNs) with different widths is challenging because, as the width increases, multiple model properties change simultaneously, and, inference in t…
stat.ML2020★ 5 cited
BaCOUn: Bayesian Classifers with Out-of-Distribution Uncertainty
Théo Guénais, Dimitris Vamvourellis, Yaniv Yacoby +2
Traditional training of deep classifiers yields overconfident models that are not reliable under dataset shift. We propose a Bayesian framework to obtain reliable uncertainty estim…