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20112023
most citedLearning Representations for Neural Network-Based Classification Using the Information Bottleneck Principle

200 citations · 675 across the 45 of their papers we have counts for

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5 papers · 1 filter

cs.IT2017★ 19 cited

On the Information Dimension of Multivariate Gaussian Processes

Bernhard C. Geiger, Tobias Koch

The authors have recently defined the Rényi information dimension rate of a stationary stochastic process as the entropy rate of the uniform…

eess.SY2017★ 13 cited

A Generalized Framework for Kullback-Leibler Markov Aggregation

Rana Ali Amjad, Clemens Blöchl, Bernhard C. Geiger

This paper proposes an information-theoretic cost function for aggregating a Markov chain via a (possibly stochastic) mapping. The cost function is motivated by two objectives: 1)…

cs.LG2017★ 21 cited

Semi-supervised cross-entropy clustering with information bottleneck constraint

Marek Śmieja, Bernhard C. Geiger

In this paper, we propose a semi-supervised clustering method, CEC-IB, that models data with a set of Gaussian distributions and that retrieves clusters based on a partial labeling…

cs.IT2017★ 19 cited

On the Information Dimension of Stochastic Processes

Bernhard C. Geiger, Tobias Koch

In 1959, Rényi proposed the information dimension and the -dimensional entropy to measure the information content of general random variables. This paper proposes a generalizati…

cs.IT2017★ 8 cited

Divergence Scaling of Fixed-Length, Binary-Output, One-to-One Distribution Matching

Patrick Schulte, Bernhard C. Geiger

Distribution matching is the process of invertibly mapping a uniformly distributed input sequence onto sequences that approximate the output of a desired discrete memoryless source…