We're having a meetup next week!
Meeting and Probabilistic Programming talk
Eli Sennesh will be speaking on Probabilistic Programming, and we'll have the usual chance to chat with other interesting people.
What is probabilistic programming? By analogy: if functional programming is programming with first-class functions and equational reasoning, probabilistic programming is programming with first-class distributions and Bayesian inference. All computable probability distributions can be encoded as probabilistic programs, and every probabilistic program represents a probability distribution.
What does it do? It gives a concise language for specifying complex, structured statistical models, and abstracts over the implementation details of exact and approximate inference algorithms. These models can be networked, causal, hierarchical, recursive, anything: the graph structure of the program is the generative structure of the distribution.
Who's interested? Cognitive scientists, statisticians, machine-learning specialists, and artificial-intelligence researchers.
PREREQUISITES: Know what Scheme/Lisp is, have previously heard of Bayes' Theorem and Bayesian reasoning. No calculations will be necessary during the presentation.