Generative probabilistic programming: applications and new ideas

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• Yura Perov, Oxford University
• Tuesday 18 February 2014, 11:00-12:00
• Auditorium, Microsoft Research Ltd, 21 Station Road, Cambridge, CB1 2FB.

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Probabilistic programming has recently attracted much attention in Computer Science and Machine Learning communities. I will briefly demonstrate two generative probabilistic graphics programs (models), which I contributed to develop. Then I will present ideas on two research directions I am interested in pursuing: a path to scaling up general-purpose approximate inference in probabilistic programs using parallelism, and a path to automatic programming via general-purpose approximate inference.

This is based on joint work with Frank Wood, Vikash Mansinghka, Tejas Kulkarni, Daniel Selsam, Joshua Tenenbaum, et al.

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