ANC Workshop - Michael Gutmann, Javier Alfaro

Tuesday, 13th February 2024

Self-supervised learning for Bayesian experimental design - Michael Gutmann

Abstract: The natural sciences increasingly use machine learning for data analysis. Whether the analysis of the data is successful or not, however, ultimately depends on the quality of the data; a sophisticated analysis cannot fix uninformative data. In this talk, I will show that machine learning can help not only with data analysis but also with the design of experiments to collect informative data. I will focus on methods that we have developed for the large class of simulator models which includes models of biochemical reactions, neural activity or infectious diseases to name a few examples.

Abstract:

Event type: Workshop

Date: Tuesday, 13th February

Time: 11:00

Location: G.03

Speaker(s): Michael Gutmann, Javier Alfaro

Chair/Host: Chenfei Ma