Bilkent Üniversitesi Topoloji Seminerleri
Conditional Independence and the Semigraphoid Properties
Igor Sikora
Bilkent University, Türkiye
Conditional independence is a central concept in probability. Generalizing conditional independence to arbitrary Markov categories is a natural part of developing synthetic probability theory. In this talk, we will show that it is still meaningful to introduce and work with conditional independence without conditionals. Reference: Section 12 from “A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics” by Tobias Fritz.
