Search Results for author: Aleksander Wieczorek

Found 9 papers, 2 papers with code

Inverse Learning of Symmetries

1 code implementation NeurIPS 2020 Mario Wieser, Sonali Parbhoo, Aleksander Wieczorek, Volker Roth

Our approach is based on the deep information bottleneck in combination with a continuous mutual information regulariser.

On the Difference Between the Information Bottleneck and the Deep Information Bottleneck

no code implementations31 Dec 2019 Aleksander Wieczorek, Volker Roth

The actual mutual information consists of the lower bound which is optimised in DVIB and cognate models in practice and of two terms measuring how much the former requirement $T-X-Y$ is violated.

Informed MCMC with Bayesian Neural Networks for Facial Image Analysis

no code implementations19 Nov 2018 Adam Kortylewski, Mario Wieser, Andreas Morel-Forster, Aleksander Wieczorek, Sonali Parbhoo, Volker Roth, Thomas Vetter

Computer vision tasks are difficult because of the large variability in the data that is induced by changes in light, background, partial occlusion as well as the varying pose, texture, and shape of objects.

Bayesian Inference

Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates

no code implementations6 Jul 2018 Sonali Parbhoo, Mario Wieser, Aleksander Wieczorek, Volker Roth

Estimating the causal effects of an intervention from high-dimensional observational data is difficult due to the presence of confounding.

Causal Inference

Greedy Structure Learning of Hierarchical Compositional Models

no code implementations CVPR 2019 Adam Kortylewski, Aleksander Wieczorek, Mario Wieser, Clemens Blumer, Sonali Parbhoo, Andreas Morel-Forster, Volker Roth, Thomas Vetter

In this work, we consider the problem of learning a hierarchical generative model of an object from a set of images which show examples of the object in the presence of variable background clutter.

Transfer Learning

Causal Compression

no code implementations1 Nov 2016 Aleksander Wieczorek, Volker Roth

We propose a new method of discovering causal relationships in temporal data based on the notion of causal compression.

Time Series

Bayesian Markov Blanket Estimation

no code implementations6 Oct 2015 Dinu Kaufmann, Sonali Parbhoo, Aleksander Wieczorek, Sebastian Keller, David Adametz, Volker Roth

This paper considers a Bayesian view for estimating a sub-network in a Markov random field.

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