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A Live, Multiple-Representation Probabilistic Programming Environment for Novices

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If you have a question about this talk, please contact Mariana Marasoiu.

This is a rehearsal for the presentation that Maria will give at CHI 2016 .

Abstract: Probabilistic programming languages, such as Infer.NET, attempt to unify general purpose programming with probabilistic modelling, in order to introduce a more abstract and powerful way of applying probabilistic models to real-world problems. This approach is becoming especially popular for data analytics, as many statistical techniques are more naturally expressed using such languages. However, the basic concepts of probabilistic programming differ from those of conventional programming, which means that learning such language could be a challenge even for an experienced programmer.

In this talk, I will present a live, multiple-representation environment for probabilistic programming based on the Infer.NET framework, addressing these conceptual differences and making the capabilities of probabilistic programming more accessible to students and end-user developers.

This talk is part of the Rainbow Group Seminars series.

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