Interactive graphical representation of an iterative message-passing Bayesian inference algorithm. The objective is to develop an interactive (web-based or Python) tool to graphically represent the operation of a message-passing algorithm which performs inference over a graph. The graph represents coupling between variables involved in the algorithm. Some understanding of probability theory is required to understand the underlying math, although the algorithm itself is already existing. Most of the work will consist in developing graphical representations of the underlying mathematical concepts using web-based or Python-based toolboxes, animating the steps of the message-passing algorithm, and allowing the user to graphically update some variables involved in the algorithm. Maxime Guillaud