Dan Geiger, an Israeli computer scientist, AI-researcher and Professor of Computer Science at Technion - Israel Institute of Technology. His main research is focused on the study of probabilistic models for intelligent systems, in particular, the study of Bayesian networks and their applications in Bioinformatics and in other domains.
Dan Geiger [1]

Selected Publications

• Judea Pearl, Dan Geiger, Tom Verma (1989). Conditional independence and its representations. Kybernetica, 25 pp. 33-44.
• Dan Geiger, Thomas Verma, Judea Pearl (1990). Identifying independence in Bayesian networks. Networks, 20, pp. 507-534.
• Dan Geiger, Judea Pearl (1990). Logical and algorithmic properties of independence and their application to Bayesian networks. Annals of Mathematics and Artificial Intelligence, 2, pp. 165-178.
• Dan Geiger, Azaria Paz, Judea Pearl (1993). Learning simple causal structures. International Journal of Intelligent Systems, 8, pp. 231-247.
• Dan Geiger, Judea Pearl (1993). Logical and algorithmic properties of conditional independence and graphical models. Annals of Statistics, 21, pp. 2001-2021.
• David Heckerman, Dan Geiger, Max Chickering (1995). Learning Bayesian Networks: The Combination of Knowledge and Statistical Data. Machine Learning, 20, pp. 197-243, pdf
• Max Chickering, Dan Geiger, David Heckerman (1995). On finding a cycle basis with a shortest maximal cycle. Information Processing Letters, 54. pp. 55-58, pdf
• Dan Geiger, David Heckerman (1996). Knowledge representation and inference in similarity networks and Bayesian multinets. Artificial Intelligence, Vol. 82, pp. 1-30

External Links

• The Mathematics Genealogy Project - Dan Geiger
• The AI Genealogy Project :: Dan Geiger

References

1. ^ Dan Geiger

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