Publications associées à Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method

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Robust Generalization via $\alpha$-Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

The aim of this work is to provide bounds connecting two probability measures of the same event using Rényi

\alpha

-Divergences and Sibson’s

\alpha

-Mutual Information, a generalization of respectively the Kullback-Leibler Divergence and Shannon’s Mutual ...

ETHZ2020

Mutual Information for the Stochastic Block Model by the Adaptive Interpolation Method

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A Functional Perspective on Information Measures

Mutual information in changing environments: Nonlinear interactions, out-of-equilibrium systems, and continuously varying diffusivities

The Gray-Wyner Network and Wyner's Common Information for Gaussian Sources

Mutual Information Disentangles Interactions from Changing Environments

A Comparison of optimal measurement-system design with engineering judgement for bridge load testing

Mutual information for low-rank even-order symmetric tensor estimation

Robust Generalization via $\alpha$-Mutual Information

Strengthened Information-theoretic Bounds on the Generalization Error

Entropy and mutual information in models of deep neural networks

Statistical Physics Methods for Community Detection

A Functional Perspective on Information Measures

Mutual information in changing environments: Nonlinear interactions, out-of-equilibrium systems, and continuously varying diffusivities

A Comparison of optimal measurement-system design with engineering judgement for bridge load testing

The Gray-Wyner Network and Wyner's Common Information for Gaussian Sources

Entropy and mutual information in models of deep neural networks

Mutual Information Disentangles Interactions from Changing Environments

Mutual information for low-rank even-order symmetric tensor estimation

Robust Generalization via $\alpha$-Mutual Information

Statistical Physics Methods for Community Detection

Strengthened Information-theoretic Bounds on the Generalization Error