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Overview of W2d1 Bayesian Statistics Tutorial 1 Part 1
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Overview of W2d1 Bayesian Statistics Tutorial 1 Part 1

Description: We discuss the goals of the day, introduce the concept of cue combination, and Gaussian distributions, culminating in ... Description: We set up causal inference/ breakdown of ventriloquism as a problem in cue combination and culminate in ... Description: We discuss how to analytically multiply two Gaussians, build intuition for what the properties of these equations are ... Description: We wrap up the discussion of cue combination with Gaussians, and culminates with a discussion of the context for the ... Description: Xaq Pitkow closes Bayes day with the advanced uses of Description: We discuss how the problem is equivalent to the problem in

Description: The posterior probability distributions we calculated in Description: We discuss the general properties of the causal inference problem and summarize the role of Causal Inference ... Megan Peters, John Krakauer, Eric DeWitt, hosted by Konrad Kording answer your questions about Athena Akrami and John Krakauer, hosted by Konrad Kording, answer your questions about Athena Akrami, Kenji Doya, Hang Zhang, hosted by Eric DeWitt answer your questions about In the first workshop of this series we discuss the basic concepts of conditional probability, Bayes Rule and