Inference on Random Factor Graphs

Random factor graphs have become a key ingredient of probabilistic constructions for tackling inference problems such as decoding, compressed sensing or group testing. I am going to present some general results about the information-theoretic aspects of such inference problems, which are closely related to understanding the replica symmetric phase of spin systems on random graphs. In addition, I am going to mention some open algorithmic problems.