Result 1 to 20 of 21 total
Bayesian networks and influence diagrams. A guide to construction and analysis. (English)
Information Science and Statistics. New York, NY: Springer (ISBN 978-0-387-74100-0/hbk). xvii, 318~p. EUR~64.95/net; SFR~113.50; \sterling~50.00; \$~79.95 (2008).
1
Applications of HUGIN to diagnosis and control of autonomous vehicles. (English)
Lucas, Peter (ed.) et al., Advances in probabilistic graphical models. Selected papers based on the presentations at the 2nd European workshop on probabilistic graphical models (PGM 2004), Leiden, The Netherlands, October 4‒8, 2004. Berlin: Springer (ISBN 978-3-540-68994-2/bhk). Studies in Fuzziness and Soft Computing 213, 313-332 (2007).
2
The hugin tool for probabilistic graphical models. (English)
Int. J. Artif. Intell. Tools 14, No. 3, 507-544 (2005).
3
The Hugin tool for learning Bayesian networks. (English)
Nielsen, Thomas Dyhre (ed.) et al., Symbolic and quantitative approaches to reasoning with uncertainty. 7th European conference, ECSQARU 2003, Aalborg, Denmark, July 2‒5, 2003. Proceedings. Berlin: Springer (ISBN 3-540-40494-5/pbk). Lect. Notes Comput. Sci. 2711, 594-605 (2003).
4
The hugin tool for learning Bayesian networks (English)
ECSQARU, 594-605 (2003).
5
UAI ’03, Proceedings of the 19th conference in uncertainty in artificial intelligence, Acapulco, Mexico, August 7-10 2003 (English)
UAI (2003).
6
Hugin - the tool for Bayesian networks and influence diagrams (English)
Probabilistic Graphical Models (2002).
7
The SACSO methodology for troubleshooting complex systems. (English)
(AI EDAM) Artificial Intelligence for Engineering Design, Analysis and Manufacturing 15, No.4, 321-333 (2001).
8
The SACSO methodology for troubleshooting complex systems (English)
AI EDAM 15, No. 4, 321-333 (2001).
9
The SACSO system for troubleshooting of printing systems (English)
SCAI, 67-79 (2001).
10
Printer troubleshooting using Bayesian networks (English)
IEA/AIE, 367-379 (2000).
11
Making sensitivity analysis computationally efficient (English)
UAI, 317-325 (2000).
12
Using robdds for inference in Bayesian networks with troubleshooting as an example (English)
UAI, 426-435 (2000).
13
Inference in Bayesian networks using nested junction trees. (English)
Jordan, Michael I. (ed.), Learning in graphical models. Proceedings of the NATO ASI, Ettore Maiorana Centre, Erice, Italy, September 27 - October 7, 1996. Dordrecht: Kluwer Academic Publishers. NATO ASI Series. Series D. Behavioural and Social Sciences. 89, 51-74 (1998).
14
Nested junction trees (English)
UAI, 294-301 (1997).
15
Blocking Gibbs sampling in very large probabilistic expert systems. (English)
Int. J. Hum.-Comput. Stud. 42, No. 6, 647-666 (1995).
16
HUGS: combining exact inference and Gibbs sampling in junction trees (English)
UAI, 368-375 (1995).
17
Reduction of computational complexity in Bayesian networks through removal of weak dependences (English)
UAI, 374-382 (1994).
18
Hybrid propagation in junction trees (English)
IPMU, 87-97 (1994).
19
A computational scheme for reasoning in dynamic probabilistic networks (English)
UAI, 121-129 (1992).
20
Result 1 to 20 of 21 total
Start
Contact
Print
General Help
