![[Search]](/static/images/search.gif){kind=small}
![[A-Z Index]](/static/images/az.gif){kind=small}
![[Contact]](/static/images/contact.gif){kind=small}
![[University of Cambridge]](/static/images/identifier2.gif){kind=small}
![[Talks.cam]](/static/images/talkslogosmall.gif)
Thursday 14 March 2013, 15:00-16:30
Probabilistic Programming
- đ¤ Speaker: James Lloyd (University of Cambridge)
- đ Date & Time: Thursday 14 March 2013, 15:00 - 16:30
- đ Venue: Engineering Department, CBL Room 438
Abstract
What is the most general class of statistical models? And how can we perform inference without designing custom algorithms? Just as automated inference algorithms make working with graphical models easy (e.g. BUGS ), a new class of automated inference procedures is being developed for the more general case of Turing-complete generative models. In this tutorial, we introduce the practice of specifying generative models as programs which produce a stochastic output, and then automatically performing inference on the execution trace of that program, conditioned on the algorithm having produced a specific output. We give examples of how to specify complex models and run inference in several ways, including recent advances in automatic Hamiltonian Monte Carlo and variational inference.
Readers who wish to familiarize themselves with these ideas beforehand are encouraged to browse around at: http://probabilistic-programming.org/wiki/Home and http://projects.csail.mit.edu/church/wiki/Church
Series This talk is part of the Machine Learning Reading Group @ CUED series.
Included in Lists
- All Talks (aka the CURE list)
- bld31
- Cambridge Centre for Data-Driven Discovery (C2D3)
- Cambridge Forum of Science and Humanities
- Cambridge Language Sciences
- Cambridge talks
- Cambridge University Engineering Department Talks
- Centre for Smart Infrastructure & Construction
- Chris Davis' list
- Computational Continuum Mechanics Group Seminars
- custom
- Engineering Department, CBL Room 438
- Featured lists
- Guy Emerson's list
- Hanchen DaDaDash
- Inference Group Journal Clubs
- Inference Group Summary
- Information Engineering Division seminar list
- Interested Talks
- Machine Learning Reading Group
- Machine Learning Reading Group @ CUED
- Machine Learning Summary
- ML
- ndk22's list
- ob366-ai4er
- Quantum Matter Journal Club
- Required lists for MLG
- rp587
- School of Technology
- Simon Baker's List
- TQS Journal Clubs
- Trust & Technology Initiative - interesting events
- yk373's list
- yk449
Note: Ex-directory lists are not shown.