3 papers
stat.ML2019
Semi-Conditional Normalizing Flows for Semi-Supervised Learning
Andrei Atanov, Alexandra Volokhova, Arsenii Ashukha +2
This paper proposes a semi-conditional normalizing flow model for semi-supervised learning. The model uses both labelled and unlabeled data to learn an explicit model of joint dist…
stat.ML2018
The Deep Weight Prior
Andrei Atanov, Arsenii Ashukha, Kirill Struminsky +2
Bayesian inference is known to provide a general framework for incorporating prior knowledge or specific properties into machine learning models via carefully choosing a prior dist…
stat.ML2018
Uncertainty Estimation via Stochastic Batch Normalization
Andrei Atanov, Arsenii Ashukha, Dmitry Molchanov +2
In this work, we investigate Batch Normalization technique and propose its probabilistic interpretation. We propose a probabilistic model and show that Batch Normalization maximaze…