Information Geometry and its Applications III

Abstract Jim Smith

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Jim Smith  (The University of Warwick, United Kingdom)
Friday, August 06, 2010, room Hörsaal 2
The algebra of causal trees and chain event graphs

One of the most flexible ways of representing families of discrete probability distributions is through event trees and the chain event graph. These are also extremely useful for representing causal hypotheses. In this talk I will show how the algebra associated with event tree families is less constrained and therefore more expressive than its Bayesian Network competitor. I will illustrate how an understanding of the algebraic features of these models gives insight into their underlying structure.

Date and Location

August 02 - 06, 2010
University of Leipzig
Augustusplatz
04103 Leipzig
Germany

Scientific Organizers

Nihat Ay
Max Planck Institute for Mathematics in the Sciences
Information Theory of Cognitive Systems Group
Germany
Contact by Email

Paolo Gibilisco
Università degli Studi di Roma "Tor Vergata"
Facoltà di Economia
Italy
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František Matúš
Academy of Sciences of the Czech Republic
Institute of Information Theory and Automation
Czech Republic
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Scientific Committee

Shun-ichi Amari
RIKEN
Brain Science Institute, Mathematical Neuroscience Laboratory
Japan
Contact by Email

Imre Csiszár
Hungarian Academy of Sciences
Alfréd Rényi Institute of Mathematics
Hungary
Contact by Email

Dénes Petz
Budapest University of Technology and Economics
Department for Mathematical Analysis
Hungary
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Giovanni Pistone
Collegio Carlo Alberto, Moncalieri
Italy
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Administrative Contact

Antje Vandenberg
Max Planck Institute for Mathematics in the Sciences
Contact by Email
Phone: (++49)-(0)341-9959-552
Fax: (++49)-(0)341-9959-555

05.04.2017, 12:42