A note on the unbiased estimation of mutual information

05/18/2021

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Estimators for mutual information are typically biased. However, in the case of the Kozachenko-Leonenko estimator for metric spaces, a type of nearest neighbour estimator, it is possible to calculate the bias explicitly.

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A note on the unbiased estimation of mutual information

On Study of Mutual Information and its Estimation Methods

Estimating mutual information for spike trains: a bird song example

Estimating the Mutual Information between two Discrete, Asymmetric Variables with Limited Samples

Learning Unbiased Representations via Mutual Information Backpropagation

fastMI: a fast and consistent copula-based estimator of mutual information

Learning Not to Learn: Training Deep Neural Networks with Biased Data

Neural Capacity Estimators: How Reliable Are They?

A note on the unbiased estimation of mutual information

Related Research

On Study of Mutual Information and its Estimation Methods

Estimating mutual information for spike trains: a bird song example

Estimating the Mutual Information between two Discrete, Asymmetric Variables with Limited Samples

Learning Unbiased Representations via Mutual Information Backpropagation

fastMI: a fast and consistent copula-based estimator of mutual information

Learning Not to Learn: Training Deep Neural Networks with Biased Data

Neural Capacity Estimators: How Reliable Are They?