This paper addresses the problem of state estimation in the case where the prior distribution of the states is not perfectly known but instead is parameterized by some unknown par...
Alternating Gibbs sampling is the most common scheme used for sampling from Restricted Boltzmann Machines (RBM), a crucial component in deep architectures such as Deep Belief Netw...
Guillaume Desjardins, Aaron C. Courville, Yoshua B...
Markov Random Fields (MRF's) can be used for a wide variety of vision problems. In this paper we focus on MRF's with two-valued clique potentials, which form a generaliz...
We present an approach to detect anatomical structures by configurations of interest points, from a single example image. The representation of the configuration is based on Markov...
— This paper describes a view-based localization method in outdoor environments. An important issue in viewbased localization is to cope with the change of object views due to ch...