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Edward: A Library for Probabilistic Modeling, Inference, and Criticism

PDE and Applied Math Seminar

Speaker: Matt Hoffman, Google
Related Webpage: http://matthewdhoffman.com/
Location: 1147 MSB
Start time: Fri, Jun 2 2017, 4:10PM

Probabilistic modeling is a powerful approach for analyzing empirical information. In this talk, I will provide an overview of Edward, a software library for probabilistic modeling. Formally, Edward is a probabilistic programming system built on computational graphs, supporting compositions of both models and inference for flexible experimentation. For example, Edward makes it easy to fit the same model using a variety of composable inferences, ranging from point estimation, to variational inference, to MCMC. Edward is also integrated into TensorFlow, providing significant speedups over existing probabilistic systems.