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VERSION:2.0
PRODID:-//Memento EPFL//
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SUMMARY:Markovian analysis of Zebrafish swimming
DTSTART:20260610T143000
DTEND:20260610T153000
DTSTAMP:20260528T052300Z
UID:e0bd55160e0108609c90fa5fe302509991534de0a8771179a68f77ae
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Mattéo Dommanget-Kott <matteo.dommanget-kott@sorbonne-
 universite.fr> \nAbstract :\nIn this interactive Python tutorial\, we wil
 l learn how Markovian frameworks can be used to analyze and model spontane
 ous locomotion from behavioral time series. We will use zebrafish reorient
 ation behavior as example.\nStarting from discrete swim-bout sequences\, w
 e will introduce Markov chains as tools for quantifying transition structu
 re\, behavioral persistence\, and temperature-dependent changes in explora
 tory strategies. \nIf time allows\, we will then extend this approach to 
 Hidden Markov Models\, showing how latent behavioral states can be inferre
 d directly from continuous kinematic observations. 
LOCATION:GA 3 21 https://plan.epfl.ch/?room==GA%203%2021
STATUS:CONFIRMED
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