73 citations · 104 across the 8 of their papers we have counts for
3 papers · 1 filter
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…
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…
A general method for regularizing tensor decomposition methods via pseudo-data
Omer Gottesman, Weiwei Pan, Finale Doshi-Velez
Tensor decomposition methods allow us to learn the parameters of latent variable models through decomposition of low-order moments of data. A significant limitation of these algori…