Exploring Synthetic Topology in Homotopy Type Theory for Probabilistic Programming πŸš€

Discover how Bas Spitters applies synthetic topology within Homotopy Type Theory to advance probabilistic programming techniques. Join the Categorical Probability and Statistics workshop 2020 for insights into cutting-edge research.

Exploring Synthetic Topology in Homotopy Type Theory for Probabilistic Programming πŸš€
Paolo Perrone
338 views β€’ Jun 7, 2020
Exploring Synthetic Topology in Homotopy Type Theory for Probabilistic Programming πŸš€

About this video

Talk at the Categorical Probability and Statistics workshop 2020:
http://perimeterinstitute.ca/personal/tfritz/2019/cps_workshop/

Title: Synthetic topology in Homotopy Type Theory for probabilistic programming
Speaker: Bas Spitters
Chair: Prakash Panangaden
Date: June 7th, 2020

Abstract:
The ALEA Coq library formalizes measure theory based on a variant of the Giry monad on the category of sets. This enables the interpretation of a probabilistic programming language with primitives for sampling from discrete distributions. However, continuous distributions have to be discretized because the corresponding measures cannot be defined on all subsets of their carriers. This paper proposes the use of synthetic topology to model continuous distributions for probabilistic computations in type theory. We study the initial Οƒ-frame and the corresponding induced topology on arbitrary sets. Based on these intrinsic topologies we define valuations and lower integrals on sets, and prove versions of the Riesz and Fubini theorems. We then show how the Lebesgue valuation, and hence continuous distributions, can be constructed.

Martin E. Bidlingmaier, Florian Faissole, Bas Spitters
arXiv:1912.07339

Video Information

Views

338

Likes

5

Duration

45:35

Published

Jun 7, 2020

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