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IDS.190 Topics in Bayesian Modeling and Computation
Probabilistic Modeling meets Deep Learning using TensorFlow Probability
September 18, 2019 @ 4:00 pm - 5:00 pm
Brian Patton (Google AI)
E18-304
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IDS.190 – Topics in Bayesian Modeling and Computation
Speaker:
Brian Patton (Google AI)
Abstract:
TensorFlow Probability provides a toolkit to enable
researchers and practitioners to integrate uncertainty with
gradient-based deep learning on modern accelerators. In this talk
we’ll walk through some practical problems addressed using TFP;
discuss the high-level interfaces, goals, and principles of the
library; and touch on some recent innovations in describing
probabilistic graphical models. Time-permitting, we may touch on a
couple areas of research interest for the team.
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**Taking IDS.190 satisfies the seminar requirement for students in MIT’s Interdisciplinary Doctoral Program in Statistics (IDPS), but formal registration is open to any graduate student who can register for MIT classes. For more information and an up-to-date schedule, please see https://stellar.mit.edu/S/course/IDS/fa19/IDS.190/
**Meetings are open to any interested researcher.
