We describe our experience using PARED, an object oriented system for the adaptive solution of PDEs in a distributed computing environment. PARED handles selective mesh refinement...
We give a notation and a logical calculus for the description and deductive manipulation of dynamic networks of communicating components. We represent such nets by hierarchical sys...
We characterize probabilities in Bayesian networks in terms of algebraic expressions called quasi-probabilities. These are arrived at by casting Bayesian networks as noisy AND-OR-...
An important class of continuous Bayesian networks are those that have linear conditionally deterministic variables (a variable that is a linear deterministic function of its pare...
The paper presents a new sampling methodology for Bayesian networks that samples only a subset of variables and applies exact inference to the rest. Cutset sampling is a network s...