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8-9 Oct 2018: Training
9-11 Oct 2018: Tutorials & Conference
London, UK

Frontiers of TensorFlow: Mathematics and music (sponsored by Google)

Joshua Dillon (Google Research), Wolff Dobson (Google)
14:35–15:15 Wednesday, 10 October 2018
Sponsored, TensorFlow at AI
Location: Buckingham Room - Palace Suite

What you'll learn

  • Explore TensorFlow Probability (TFP) and Project Magenta, a research project exploring the role of machine learning in the process of creating art and music

Description

TensorFlow Probability (TFP) is a TF/Python library offering a modern take on both emerging and traditional probability and statistics tools. Statisticians and data scientists will find R-like capabilities, which naturally leverage modern hardware, while ML researchers and practitioners will find powerful building blocks for specifying and learning deep, probabilistic models.

Joshua Dillon and Wolff Dobson discuss core TFP abstractions and demo some of TFP’s modeling power and convenience. They also share some of the recent results from Project Magenta, a research project exploring the role of machine learning in the process of creating art and music.

Photo of Joshua Dillon

Joshua Dillon

Google Research

Joshua V. Dillon is a software engineer for research and machine intelligence at Google. His research interests include approximate inference techniques for probabilistic models, uncertainty in machine learning, and designing probabilistic programming tools and languages. He holds a PhD in machine learning from the Georgia Institute of Technology. In his free time, Josh enjoys spending time with his family, cycling, and woodworking.

Photo of Wolff Dobson

Wolff Dobson

Google

Wolff Dobson is a developer programs engineer at Google specializing in machine learning and games. Previously, he worked as a game developer, where his projects included writing AI for the NBA 2K series and helping design the Wii Motion Plus. Wolff holds a PhD in artificial intelligence from Northwestern University.

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