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IJCAI
2007
13 years 9 months ago
Compiling Bayesian Networks by Symbolic Probability Calculation Based on Zero-Suppressed BDDs
Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
Shin-ichi Minato, Ken Satoh, Taisuke Sato
JMLR
2012
11 years 10 months ago
Bayesian regularization of non-homogeneous dynamic Bayesian networks by globally coupling interaction parameters
To relax the homogeneity assumption of classical dynamic Bayesian networks (DBNs), various recent studies have combined DBNs with multiple changepoint processes. The underlying as...
Marco Grzegorczyk, Dirk Husmeier
ECSQARU
2005
Springer
14 years 1 months ago
Hydrologic Models for Emergency Decision Support Using Bayesian Networks
In the presence of a river flood, operators in charge of control must take decisions based on imperfect and incomplete sources of information (e.g., data provided by a limited numb...
Martín Molina, Raquel Fuentetaja, Luis Garr...
KI
2010
Springer
13 years 5 months ago
Situation-Specific Intention Recognition for Human-Robot Cooperation
Recognizing human intentions is part of the decision process in many technical devices. In order to achieve natural interaction, the required estimation quality and the used comput...
Peter Krauthausen, Uwe D. Hanebeck
CSMR
2009
IEEE
14 years 8 days ago
A Method for Choosing Software Assessment Measures Using Bayesian Networks and Diagnosis
Creating accurate models of information systems is an important but challenging task. It is generally well understood that such modeling encompasses general scientific issues, bu...
Ulrik Franke, Pontus Johnson, Robert Lagerströ...