Speaker |
Jeremias Knoblauch |
|---|---|
Affiliation |
University College London |
Date |
Friday, 22 November 2024 |
Time |
11:30-12:30 |
Location |
Function Space, UCL Centre for Artificial Intelligence, 1st Floor, 90 High Holborn, London WC1V 6BH |
Link |
https://ucl.zoom.us/j/99748820264 |
Event series |
Jump Trading/ELLIS CSML Seminar Series |
Abstract |
In this talk, I provide my perspective on the machine learning community's efforts to develop inference procedures with Bayesian characteristics that go beyond Bayes' Rule as an epistemological principle. I will explain why these efforts are needed, as well as the forms which they take. Focusing on some of my own contributions to the field, I will trace out some of the community's most important milestones, as well as the challenges that lie ahead. Throughout, I will provide success stories of the field, and emphasise the new opportunities that open themselves up to us once we dare to go beyond orthodox Bayesian procedures. |
Biography |
Jeremias is an Associate Professor at UCL’s Department of Statistical Science. Prior to his current position, he was a Lecturer (07/2022-10/2024) and Biometrika Fellow in (10/2021-07/2022), also based at UCL. Before that, he was a doctoral candidate within the Oxford-Warwick Statistics programme (2016-2021) as well as the first UK-based Facebook Fellow (2020/2021). During that time, he also worked with the research arms of Amazon (2019) and DeepMind (2021). |