Denoising and Untangling Graphs Using Degree Priors

This paper addresses the problem of untangling hidden graphs from a set of noisy detections of undirected edges. We present a model of the generation of the observed graph that includes degree-based structure priors on the hidden graphs. Exact inference in the model is intractable; we present an efficient approximate inference algorithm to compute edge appearance posteriors. We evaluate our model and algorithm on a biological graph inference problem.

• Type: Conference
• Year: 2003
• Where: NIPS
• Authors: Quaid Morris, Brendan J. Frey
• Keywords: Graph Inference Problem, Hidden Graphs, NIPS 2003, NIPS 2007, Untangling Hidden Graphs