Abstract. We introduce an extended computational framework for studying biological systems. Our approach combines formalization of existing qualitative models that are in wide but ...
Irit Gat-Viks, Amos Tanay, Daniela Raijman, Ron Sh...
Ancestral graph models, introduced by Richardson and Spirtes (2002), generalize both Markov random fields and Bayesian networks to a class of graphs with a global Markov property ...
Many models of wireless sensor networks (WSNs) assume a perfect synchronization along the graph of such network as a simplifying assumption. In our contribution we base our invest...
We present a method for parameter learning in relational Bayesian networks (RBNs). Our approach consists of compiling the RBN model into a computation graph for the likelihood fun...
Abstract— In this paper, we present an optimization framework for target tracking with mobile robot teams. The target tracking problem is modeled as a generic semidefinite progr...