Building probabilistic networks: where do the numbers come from? -- a guide to the literature (2000)

by Marek J. Druzdzel , Linda C. van der Gaag
Venue:IEEE Transactions on Knowledge and Data Engineering
Citations:29 - 3 self

Active Bibliography

Building Probabilistic Networks: ªWhere Do the Numbers Come From?º Guest Editors ' Introduction – Marek J. Druzdzel, Linda C. Van Der Gaag
11 Properties of Sensitivity Analysis of Bayesian Belief Networks – Veerle M. H. Coupe, Linda C. Van Der Gaag - 1999
564 Dynamic Bayesian Networks: Representation, Inference and Learning – Kevin Patrick Murphy - 2002
27 Talking Probabilities: Communicating Probabilistic Information With Words And Numbers – Silja Renooij, Cilia Witteman - 1999
1 A Computational Architecture for N-way Sensitivity Analysis of Bayesian Networks – Veerle M.H. Coupe, Finn V. Jensen, Uffe Kjaerulff, Linda C. van der Gaag
1 Using sensitivity analysis for selective parameter update in Bayesian network learning – Haiqin Wang - 2002
9 Using Sensitivity Analysis for Efficient Quantification of a Belief Network – Veerle M. H. Coupe, Niels Peek, Jaap Ottenkamp, J. Dik F. Habbema - 1999
5 Bayesian Belief Networks: Odds and Ends – Linda C. Van Der Gaag - 1996
Does Query-Based Diagnostics Work? – Parot Ratnapinda, Marek J. Druzdzel
176 The Bayes Net Toolbox for MATLAB – Kevin P. Murphy - 2001
Bayesian Belief Networks for Dementia Diagnosis and Other Applications: A Comparison of Hand-Crafting and Construction using A Novel Data Driven Technique – Lloyd Oteniya, Lloyd Oteniya
172 A Guide to the Literature on Learning Probabilistic Networks From Data – Wray Buntine - 1996
3 Making sensitivity analysis computationally efficient – Uffe Kjærulff, Linda C. van der Gaag - 2000
A Web-based Tool for Expert Elicitation in Distributed Teams – Carlo Spaccasassi, Lea Deleris
BMAW-11 Preface Preface – unknown authors
spiina1003z/Womat/Production/PRODENV/0000000020/0000011876/0000000005/0000891534.3D Decision Support Systems – Marek J. Druzdzel, Roger R. Flynn
unknown title – Silvano Mussi
2 Quantifying the Uncertainty of a Belief Net Response: Bayesian Error-Bars for Belief Net Inference – Tim Van Allen, Ajit Singh, Russell Greiner, Peter Hooper
32 Learning Bayesian Network Parameters from Small Data Sets: Application of Noisy-OR Gates – Agnieszka Onisko, Marek J. Druzdzel, Hanna Wasyluk - 2000