MINERVA Introduces Neural Mutual Information for Feature Selection

MINERVA, a feature‑selection method, was tested on synthetic benchmarks and fraud detection data, achieving accuracy with fewer features than traditional filters. getnews.me/minerva-introduces-neura... #minerva #mutualinformation

Reliable Mutual Information Estimation for High‑Dimensional Data

A protocol merges classical and neural MI estimators, adds bootstrap confidence intervals and uses probabilistic critics for stable high‑dimensional data. Read more: getnews.me/reliable-mutual-informat... #mutualinformation #highdimensional

InfoBridge: Diffusion‑Bridge Method for Mutual Information Estimation

InfoBridge uses diffusion‑bridge models to estimate mutual information on high‑dimensional data as images and protein embeddings. The paper was posted September 2025. Read more: getnews.me/infobridge-diffusion-bri... #infobridge #mutualinformation

Mutual Information Boosts Multi‑Latent Image Generators

Researchers used mutual information to evaluate latent variables in generators, showing synthetic views match or exceed real‑image performance in contrastive learning. Code on GitHub. getnews.me/mutual-information-boost... #mutualinformation #syntheticdata

Whether you're analyzing data or optimizing models, understanding how information is distributed and shared can give you a serious edge.

#InformationTheory #MachineLearning #Entropy #MutualInformation #DataScience #AI #ML #DataAnalysis

https://openreview.net/forum?id=LdflD41Gn8

In our previous paper on benchmarking #MutualInformation estimators, we focus on going "beyond normal" distributions. However, it turns out that we can do much more, as we show in our new TMLR paper: "On the Properties and Estimation of Pointwise Mutual Information Profiles" 1/2