The key idea behind the probabilistic framework to machine learning is that learning can be thought of as inferring plausible models to explain observed data. A machine can use such models to make ...

Probability and Statistics Group research at the School of Mathematical and Computer Sciences at Heriot-Watt University, Edinburgh.

A five-minute formula from Alexander Denev that takes you through a simple probabilistic graphical model and explains how and why these are used. Find out more about the ground-breaking book, ...

A few weeks ago, I wrote an article titled, "Cultivating an Expected Return Mindset." This article is an updated version of the aforementioned.

We extend previous studies by including a general model of the recognition heuristic that considers probabilistic recognition, and carry out a mathematical analysis. We derive general closed-form ...