Learning Bayesian Networks 15 Years Later
Marco Scutari, Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), Polo Universitario Lugano
Monday 24th June 2024 3:15pm-3:45pm AEST
Marco Scutari is a Senior Researcher at Istituto Dalle Molle di Studi sull’Intelligenza Artificiale (IDSIA), one of Switzerland’s national AI research centres. Since completing his PhD in Statistics in 2011, he has held positions in Statistics Genetics (UCL), Statistics (Oxford), and Machine Learning (IDSIA) in the UK and Switzerland. His work focuses on the theory of Bayesian networks and their application to biological, environmental and clinical sciences, statistical computing, and software engineering for machine learning applications.
bnlearn (https://www.bnlearn.com/) is an R package that provides a complete solution for Bayesian network learning and inference. It started 15+ years ago as a small personal project to implement the algorithms Marco needed for his dissertation, which had no publicly available implementation. Today, bnlearn provides a comprehensive tool for both simulations and real-world data analysis. In this talk, Marco will discuss its design philosophy and his plans to tackle the main open problems in Bayesian network learning. He will use some of his ongoing data analyses as examples.