We develop an integrated probabilistic model to combine protein physical interactions, genetic interactions, highly correlated gene expression network, protein complex data, and d...
Intelligent agents offer a new and exciting way of understanding the world of work. In this paper we apply agentbased modeling and simulation to investigate a set of problems in a...
Peer-Olaf Siebers, Uwe Aickelin, Helen Celia, Chri...
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
Many problems in vision can be formulated as Bayesian inference. It is important to determine the accuracy of these inferences and how they depend on the problem domain. In recent...
Alan L. Yuille, James M. Coughlan, Song Chun Zhu, ...
This paper examines the tradeoffs between flexibility, area, and power dissipation of programmable clock networks for FieldProgrammable Gate Arrays (FPGA's). The paper begins...