41 citations · 41 across the 1 of their papers we have counts for
3 papers
The k-tied Normal Distribution: A Compact Parameterization of Gaussian Mean Field Posteriors in Bayesian Neural Networks
Jakub Swiatkowski, Kevin Roth, Bastiaan S. Veeling +7
Variational Bayesian Inference is a popular methodology for approximating posterior distributions over Bayesian neural network weights. Recent work developing this class of methods…
How Good is the Bayes Posterior in Deep Neural Networks Really?
Florian Wenzel, Kevin Roth, Bastiaan S. Veeling +7
During the past five years the Bayesian deep learning community has developed increasingly accurate and efficient approximate inference procedures that allow for Bayesian inference…
Discriminative k-shot learning using probabilistic models
Matthias Bauer, Mateo Rojas-Carulla, Jakub Bartłomiej Świątkowski +2
This paper introduces a probabilistic framework for k-shot image classification. The goal is to generalise from an initial large-scale classification task to a separate task compri…