• Brooks Paige: Variational inference in probabilistic programs. Slides for the talk [[
  • Tom Rainforth: Top-Down Particle Filtering for Bayesian Decision Trees by Balaji Lakshminarayanan, Daniel Roy, Yee Whye Teh. Slides for the talk
  • David Tolpin: Probabilistic Programming by Andrew D. Gordon, Thomas A. Henzinger, Aditya V. Nori, and Sriram K. Rajamani Slides for the talk
  • Brooks Paige: Adaptive MCMC Tutorial. Slides for the talk:
  • Jeremy Gibbons: Oleg Kiselyov, Chung-chieh Shan: Embedded Probabilistic Programming Notes for the talk:
  • David Poole: David Poole, Probabilistic Programming Languages: Independent Choices and Deterministic Systems, in Heuristics, Probability and Causality: A Tribute to Judea Pearl, edited by R. Dechter, H. Geffner and J.Y. Halpern, College Publications, 2010, pages 253-269. Slides for the talk: http://www.cs.ubc.ca/~poole/talks/IndependentChoicesTalk2014.pdf