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Introduction
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Why Causality
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Observational Data
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Data modalities
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Causality hierarchy
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Predicting interventions
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Thank you
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Story behind the drug
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Using causal discovery algorithms
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Predicting the effect of unseen interventions
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Conclusions
Description:
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

Simons Institute
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