In this paper, we aim to reconstruct free-form 3D models from only one or few silhouettes by learning the prior knowledge of a specific class of objects. Instead of heuristically...
This paper explores a formulation for attributed graph matching as an inference problem over a hidden Markov Random Field. We approximate the fully connected model with simpler mo...
Dante Augusto Couto Barone, Terry Caelli, Tib&eacu...
We present a fully probabilistic stick-figure model that uses a nonparametric Bayesian distribution over trees for its structure prior. Sticks are represented by nodes in a tree i...
Edward Meeds, David A. Ross, Richard S. Zemel, Sam...
We investigate the use of recently proposed character and word sequence kernels for the task of authorship attribution and compare their performance with two probabilistic approac...
We construct an efficient probabilistic algorithm that, given a finite set with a binary operation, tests if it is an abelian group. The distance used is an analogue of the edit d...