We describe the design, semantics, and implementation of a probabilistic programming language where programs are spreadsheet queries. Given an input database consisting of tables held in a spreadsheet, a query constructs a probabilistic model conditioned by the spreadsheet data, and returns an output database determined by inference. This work extends probabilistic programming systems in three novel aspects: embedding in spreadsheets, dependently-typed functions, and typed distinction between random- and query-variables. It empowers users with knowledge of statistical modelling to do inference simply by editing textual annotations within their spreadsheets, with no other coding.
Tue 14 AprDisplayed time zone: Azores change
Tue 14 Apr
Displayed time zone: Azores change
10:30 - 12:30 | |||
10:30 30mTalk | Probabilistic Programs as Spreadsheet Queries ESOP Andrew D. Gordon Microsoft Research and University of Edinburgh, Claudio Russo Microsoft Research, Marcin Szymczak University of Edinburgh, Johannes Borgström Uppsala University, Nicolas Rolland Microsoft Research, Thore Graepel Microsoft Research, Daniel Tarlow Microsoft Research | ||
11:00 30mTalk | Static Analysis of Spreadsheet Applications for Type-Unsafe Operations Detection ESOP | ||
11:30 30mTalk | Running Probabilistic Programs Backwards ESOP | ||
12:00 30mTalk | A Verified Compiler for Probability Density Functions ESOP Manuel Eberl Technische Universität München, Johannes Hölzl Technische Universität München, Tobias Nipkow Technische Universität München |