Abstract. A promising approach for model counting was recently introduced, which in theory requires the use of large random xor or parity constraints to obtain near-exact counts of...
As Bayesian networks become widely accepted as a normative formalism for diagnosis based on probabilistic knowledge, they are applied to increasingly larger problem domains. These...
Yanping Xiang, Kristian G. Olesen, Finn Verner Jen...
We propose a novel representation for characterizing image differences using a deformable technique for obtaining pixel-wise correspondences. This representation, which is based o...
: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
Strong and weak simulation relations have been proposed for Markov chains, while strong simulation and strong probabilistic simulation relations have been proposed for probabilisti...
Lijun Zhang, Holger Hermanns, Friedrich Eisenbrand...