Discrete Applied Math Seminar By Miles Bakenhus: Conditional Independence Models for Random Graphs




Online Seminar

Social Media Links


Miles Bakenhus, Ph.D. candidate, Illinois Institute of Technology


Conditional Independence Models for Random Graphs


Conditional independence models are used across a variety of fields to describe relationships between random variables. While many random graph models assume that edges occur independently of each other, this is often not the case in real world examples. For instance, edges in social networks may exhibit transitivity and degree correlation, both of which can lead to dyadic dependence. This presentation will cover a brief background to random graph models as well as the concepts of conditional independence and dyadic dependency. Some examples of traditional random graph models, modified to include dyadic dependency will be shown with their distributions. In addition, the algebraic structure of conditional independence models will be discussed, with methods that may be used to sample from these models.


The Discrete Applied Math seminar will be held most Fridays from 3:30 p.m. - 4:30 p.m. on Zoom during the Spring 2022 semester.


Discrete Applied Math seminar


Event Contact

Hemanshu Kaul
Co-Director, M.S. in Computational Decision Science and Operations Research (CDSOR) Associate Professor of Applied Mathematics

Getting to Campus