Yair Weiss Hebrew University Approximate inference in graphical models using loopy belief propagation I will discuss the problem of approximate inference in graphical models and describe an algorithm that has recently been used in a number of applications: loopy belief propagation. I will describe some empirical success stories of this algorithm as well as summarize what is known theoretically about the algorithm. Yair Weiss is a senior lecturer at the Hebrew University School of Computer Science and Engineering. He received his Ph.D. from the Massachusetts Institute of Technology and was a visiting scientist at U.C. Berkeley. His research interests include human and machine vision, machine learning and error correcting codes.