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AIC Seminar Series

Probabilistic programming: ideas and algorithms

Andreas StuhlmüllerMIT Department of Brain and Cognitive Sciences[Home Page]

Notice:  Hosted by Rodrigo Braz

Date:  2014-02-20 at 16:00

Location:  EK255 (SRI E building)  (Directions)

Webex: 

VTC connection with SRI San Diego
   Abstract

Probabilistic programming is a recent merger between programming languages and Bayesian statistics that enables rapid development of complexly structured probabilistic models. I will give a practical introduction to the key ideas and algorithms of the field using the probabilistic programming language Church. I will describe some of the cognitive science applications that motivated the development of this language, and I will outline our current research on amortized inference.

   Bio for Andreas Stuhlmüller

I am a Ph.D. student in the Department of Brain and Cognitive Sciences at MIT. I work in Josh Tenenbaum’s Computational Cognitive Science group and in Noah Goodman’s Computation & Cognition lab at Stanford.

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