Graphical modelling and network inference

Bayes' Theorem 2D

Johannes Berg and David Gross

Inverse problems in statistical physics are motivated by the challenges `big data' in different fields, especially high-throughput experiments in biology. Key question is how to infer parameters of a model which describes the statistics of the data and how to link those parameters to the processes generating data. In this seminar, we focus on network inference using Bayesian networks and explore links to both statistical and quantum physics.

Specific topics include

This seminar is part of the StatBio module of the Master's in Physics.


Friday 12:00, Seminar Room I Physical Institute