Exploring the Limits of the Bayesian Universe: How to Tackle Breadth and Depth.
Date: Tuesday, 8 November 2022
Time: 8:00 (UTC)
Speaker: A/Prof. Aaron Robotham (University of Western Australia)
Contact the organizer: Andriy Olenko a.olenko@latrobe.edu.au
Abstract:
In the last 10 years it is notable that students are much more enthused about projects involving “machine learning”, but it is important we do not lose perspective on the scientific insights still offered by a comprehensive and pragmatic application of Bayesian principles. Here I will discuss the work my group has undertaken over the last 7 years to build up a fully generative model of galaxies that has culminated in the Bayesian modelling software ProFuse (Robotham+ 2022). The positive is that encoding our knowledge and ignorance in a Bayesian manner has opened up new insights to physical processes that form galaxies, the negative is that this approach has a high barrier of entry which can be a poor fit to a modern ~3 year PhD.
Stefano Andreon - INAF-OA Brera, Italy (chair) Fabio Castagna - INAF-OA Brera, University of Insubria, Italy Andriy Olenko - La Trobe University, Australia Tsutomu T. Takeuchi - Nagoya University, Japan