Pablo Ibieta

Notes on data science, machine learning, physics, information theory, econometrics, and causal inference.

Conditional mutual information is just log-loss gain

information-theory

machine-learning

simulation

cmi-framework

Two models, a subtraction, and you’ve estimated an information-theoretic quantity. The identity that makes CMI cheap to compute — and the first post in a short series on the CMI framework.

Welcome

meta

What this blog is for, and how it’s put together.

Mutual information sees what correlation can’t

information-theory

statistics

simulation

A short note on why mutual information is the right generalization of Pearson correlation — and a simulation that shows the gap.

---
title: "Pablo Ibieta"
subtitle: "Notes on data science, machine learning, physics, information theory, econometrics, and causal inference."
listing:
  contents: posts
  sort: "date desc"
  type: default
  categories: true
  sort-ui: [date, title, reading-time]
  filter-ui: true
  feed: true
  fields: [date, title, reading-time, description, categories]
  page-size: 15
page-layout: full
title-block-banner: false
---