Residual Belief Propagation and Beyond

Project Type: Master/Diploma Thesis
Student: Michalel Rath


Short Description

Loopy belief propagation is well established for performing approximate inference in loopy graphs. Recently, residual belief propagration has been introduced. It has been shown that asynchronous message scheduling is beneficial to synchronous message passing. The aim of this thesis is to investigate the convergence behaviour of various message passing scheduling schemes. Furthermore, alternatives should be developed.



Your Profile/Requirements

The candidate should be interested in machine learning, applied mathematics/statistics, Matlab programming, and algorithms. Interested candidates are encouraged to ask for further information. Additionally, the supervision of own projects in one of the above mention fields is possible.


Franz Pernkopf ( or 0316/873 4436)