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SUMMARY:Caroline Uhler (MIT)
DTSTART:20200918T150500Z
DTEND:20200918T160500Z
DTSTAMP:20260423T004730Z
UID:sss/5
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/sss/5/">Caus
 al Inference and Overparameterized Autoencoders in the Light of Drug Repur
 posing for SARS-CoV-2</a>\nby Caroline Uhler (MIT) as part of Stochastics 
 and Statistics Seminar Series\n\n\nAbstract\nMassive data collection holds
  the promise of a better understanding of complex phenomena and ultimately
 \, of better decisions. An exciting opportunity in this regard stems from 
 the growing availability of perturbation / intervention data (drugs\, knoc
 kouts\, overexpression\, etc.) in biology. In order to obtain mechanistic 
 insights from such data\, a major challenge is the development of a framew
 ork that integrates observational and interventional data and allows predi
 cting the effect of yet unseen interventions or transporting the effect of
  interventions observed in one context to another. I will present a framew
 ork for causal inference based on such data and particularly highlight the
  role of overparameterized autoencoders. We end by demonstrating how these
  ideas can be applied for drug repurposing in the current SARS-CoV-2 crisi
 s.\n
LOCATION:https://researchseminars.org/talk/sss/5/
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