12 citations · 16 across the 5 of their papers we have counts for
5 papers
Optimizing Causal Orderings for Generating DAGs from Data
Remco R. Bouckaert
An algorithm for generating the structure of a directed acyclic graph from data using the notion of causal input lists is presented. The algorithm manipulates the ordering of the v…
A Stratified Simulation Scheme for Inference in Bayesian Belief Networks
Remco R. Bouckaert
Simulation schemes for probabilistic inference in Bayesian belief networks offer many advantages over exact algorithms; for example, these schemes have a linear and thus predictabl…
Properties of Bayesian Belief Network Learning Algorithms
Remco R. Bouckaert
Bayesian belief network learning algorithms have three basic components: a measure of a network structure and a database, a search heuristic that chooses network structures to be c…
Error Estimation in Approximate Bayesian Belief Network Inference
Enrique F. Castillo, Remco R. Bouckaert, Jose M. Sarabia +1
We can perform inference in Bayesian belief networks by enumerating instantiations with high probability thus approximating the marginals. In this paper, we present a method for de…
On characterizing Inclusion of Bayesian Networks
Tomas Kocka, Remco R. Bouckaert, Milan Studeny
Every directed acyclic graph (DAG) over a finite non-empty set of variables (= nodes) N induces an independence model over N, which is a list of conditional independence statements…