2017
Sequential Graph Matching with Sequential Monte Carlo
AISTATS 2017poster
We develop a novel probabilistic model for graph matchings and develop practical inference methods for supervised and unsupervised learning of the parameters of this model. The framework we develop admits joint inference on the parameters and the matching. Furthermore, our framework generalizes natu…