Explore the intersection of causality and autoencoders in the context of drug repurposing for COVID-19 in this Richard M. Karp Distinguished Lecture by Caroline Uhler from MIT. Delve into the importance of causality, observational data, and various data modalities. Examine the causality hierarchy and learn how to predict interventions. Discover the story behind drug repurposing and understand the application of causal discovery algorithms. Gain insights into predicting the effects of unseen interventions and draw valuable conclusions from this comprehensive 57-minute talk presented at the Simons Institute.
Causality and Autoencoders in Light of Drug Repurposing for COVID-19
Overview
Syllabus
Introduction
Why Causality
Observational Data
Data modalities
Causality hierarchy
Predicting interventions
Thank you
Story behind the drug
Using causal discovery algorithms
Predicting the effect of unseen interventions
Conclusions
Taught by
Simons Institute
