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SUMMARY:Causal Discovery from Observations: Introduction and Some Recent A
 dvances - Mario Figueiredo
DTSTART:20231110T150000Z
DTEND:20231110T160000Z
UID:TALK208225@talks.cam.ac.uk
CONTACT:Matthew Colbrook
DESCRIPTION:In causal discovery\, the aim is to uncover the underlying cau
 sal mechanisms that drive the relationships between a collection of observ
 ed variables. It is a research topic with applications in many areas\, inc
 luding medicine\, biology\, economics\, and social sciences. In principle\
 , identifying causal relationships requires interventions (a.k.a.\, experi
 ments). However\, this is often impossible\, impractical\, or unethical\, 
 which has stimulated much research on causal discovery from purely observa
 tional data or mixed observational-interventional data. In this talk\, aft
 er surveying the causal discovery field\, I will discuss some recent advan
 ces\, namely on causal discovery from data with latent interventions and o
 n the quintessential causal discovery problem: distinguishing cause from e
 ffect on a pair of dependent variables.\n
LOCATION:Centre for Mathematical Sciences\, MR15
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