Given an expression that denotes a probability distribution, often we want a corresponding density function, to use in probabilistic inference. Fortunately, the task of finding a density has been automated. It turns out that we can derive a compositional procedure for finding a density, by equational reasoning about integrals, starting with the mathematical specification of what a density is. Moreover, the density found can be run as an estimation algorithm, as well as simplified as an exact formula to improve the estimate.
Mon 19 SepDisplayed time zone: Osaka, Sapporo, Tokyo change
Mon 19 Sep
Displayed time zone: Osaka, Sapporo, Tokyo change
10:45 - 12:25 | |||
10:45 25mTalk | Farms, Pipes, Streams and Reforestation: Reasoning about Structured Parallel Processes using Types and Hylomorphisms Research Papers David Castro-Perez University of St. Andrews, UK, Kevin Hammond University of St. Andrews, UK, Susmit Sarkar University of St. Andrews, UK DOI | ||
11:10 25mTalk | Dag-Calculus: A Calculus for Parallel Computation Research Papers Umut A. Acar Carnegie Mellon University, Arthur Charguéraud Inria, France, Mike Rainey Inria, France, Filip Sieczkowski Inria, France DOI | ||
11:35 25mTalk | A Lambda-Calculus Foundation for Universal Probabilistic Programming Research Papers Johannes Borgström Uppsala University, Sweden, Ugo Dal Lago University of Bologna, France, Andrew D. Gordon Microsoft Research, UK, Marcin Szymczak University of Edinburgh, UK DOI | ||
12:00 25mTalk | Deriving a Probability Density Calculator (Functional Pearl) Research Papers DOI | ||