Conference item
Categorical information geometry
- Abstract:
- Information geometry is the study of interactions between random variables by means of metric, divergences, and their geometry. Categorical probability has a similar aim, but uses algebraic structures, primarily monoidal categories, for that purpose. As recent work shows, we can unify the two approaches by means of enriched category theory into a single formalism, and recover important information-theoretic quantities and results, such as entropy and data processing inequalities.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
Actions
Access Document
- Files:
-
-
(Preview, Accepted manuscript, pdf, 363.5KB, Terms of use)
-
- Publisher copy:
- 10.1007/978-3-031-38271-0_27
Authors
- Publisher:
- Springer
- Host title:
- Geometric Science of Information. GSI 2023
- Pages:
- 268-277
- Series:
- Lecture Notes in Computer Science
- Series number:
- 14071
- Place of publication:
- Cham, Switzerland
- Publication date:
- 2023-08-01
- Acceptance date:
- 2023-04-28
- Event title:
- Geometric Science of Information 6th International Conference (GSI 2023)
- Event location:
- St. Malo, France
- Event website:
- https://conference-gsi.org/
- Event start date:
- 2023-08-30
- Event end date:
- 2023-09-01
- DOI:
- EISSN:
-
1611-3349
- ISSN:
-
0302-9743
- EISBN:
- 9783031382710
- ISBN:
- 9783031382703
- Language:
-
English
- Keywords:
- Pubs id:
-
1548189
- Local pid:
-
pubs:1548189
- Deposit date:
-
2024-05-09
- ARK identifier:
Terms of use
- Copyright holder:
- Paolo Perrone
- Copyright date:
- 2023
- Rights statement:
- © 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG.
- Notes:
- This is the accepted manuscript version of the paper. The final version is available online from Springer at https://dx.doi.org/10.1007/978-3-031-38271-0_27
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