http://anglican.ml/, the proper domain for the Anglican way of machine learning.
October 7, 2016
October 8, 2015
Immanuel Kant and Probability
Kant said: there are two a priori intuitions — space and time. There are also categories, and “the number of the categories in each class is always the same, namely, three”, like unity-plurality-modality, or possibility-existence-necessity. It would be fun to have three a priori intuitions, but only two exist, sigh. Really though?
(more…)
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June 10, 2015
Maximum a Posteriori Estimation by Search in Probabilistic Programs
Paper, slides, and poster as presented at SOCS 2015.
We introduce an approximate search algorithm for fast maximum a posteriori probability estimation in probabilistic programs, which we call Bayesian ascent Monte Carlo (BaMC). (more…)
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June 8, 2015
Path Finding under Uncertainty through Probabilistic Inference
An early workshop paper, superseded by current research but still relevant, slides, and a poster.
Abstract
We introduce a new approach to solving path-finding problems under uncertainty by representing them as probabilistic models and applying domain-independent inference algorithms to the models. (more…)
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May 6, 2015
Anglican the Probabilistic Programming Concept
Anglican is a probabilistic programming language, or better yet, a concept, living in symbiosis with Clojure. Anglican stands for Church of England (because we are here in Oxford). To create your Turing-complete probabilistic models, clone anglican-user and hack away. Or, look at cool examples.
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December 10, 2014
Output-Sensitive Adaptive MH for Probabilistic Programs
A poster for the 3rd NIPS Workshop on Probabilistic Programming; also available as A0 PDF. Slides for a 15-minute talk.
Abstract
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