3 papers
cs.LG2026
Geometric and Information Compression of Representations in Deep Learning
Linara Adilova, Henning Petzka, Asja Fischer +1
Deep neural networks transform input data into latent representations that support a wide range of downstream tasks. These representations can be characterized along information-th…
cs.IT2026
Universal Outlier Hypothesis Testing via Mean- and Median-Based Tests
Bernhard C. Geiger, Tobias Koch, Josipa MihaljeviÄ +1
Universal outlier hypothesis testing refers to a hypothesis testing problem where one observes a large number of length- sequences -- the majority of which are distributed accor…
cs.LG2025
On the Role of Priors in Bayesian Causal Learning
Bernhard C. Geiger, Roman Kern
In this work, we investigate causal learning of independent causal mechanisms from a Bayesian perspective. Confirming previous claims from the literature, we show in a didactically…