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SUMMARY:Mário Figueiredo (Instituto Superior Técnico and IT)
DTSTART:20230615T160000Z
DTEND:20230615T170000Z
DTSTAMP:20260423T003233Z
UID:MPML/109
DESCRIPTION:Title: <a href="https://researchseminars.org/talk/MPML/109/">C
 ausal Discovery from Observations: Introduction and Some Recent Advances</
 a>\nby Mário Figueiredo (Instituto Superior Técnico and IT) as part of M
 athematics\, Physics and Machine Learning (IST\, Lisbon)\n\n\nAbstract\nCa
 usal discovery is an active research field that aims to uncover the underl
 ying causal mechanisms that drive the relationship between a collection of
  variables and which has applications in many areas\, including medicine\,
  biology\, economics\, and social sciences. In principle\, identifying cau
 sal relationships requires interventions. However\, intervening is often i
 mpossible\, impractical\, or unethical\, which has stimulated much researc
 h on causal discovery from purely observational data or mixed observationa
 l-interventional data. In this talk\, after overviewing the causal discove
 ry field\, I will discuss some recent advances\, namely on causal discover
 y from data with latent interventions and on what is the quintessential ca
 usal discovery problem: distinguishing the cause from the effect on a pair
  of dependent variables.\n
LOCATION:https://researchseminars.org/talk/MPML/109/
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