Probabilistic similarity networks

By David E. Heckerman. Networks, 2019

371 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b64851333008e6331f8815619c5a513a3354c9c9

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Citations in the corpus

A Bayesian framework for combining heterogeneous data sources for gene function prediction (in Saccharomyces cerevisiae) (2003, unknown): “22).”
Building large-scale Bayesian networks (2000, background): “260 We do not review all of the tricks and tips that might help the practitioner build BNs in practice, like noisy-OR (Jensen, 1996) or the partitioning of probability tables (Heckerman, 1990).”
Bayesian Network Classifiers (1997, background): “The set of local networks combined with a prior on C , P ( C ) , is called a Bayesian multinet (Heckerman, 1991; Geiger & Heckerman, 1996).”
Bayesian Networks and Decision Graphs (2001, methodology): “A method not described in this chapter is similarity networks (Heckerman 1990).”
Learning with Graphical Models (1994, methodology): “One technique is to decompose and structure the problem carefully to reduce complexity, for instance using similarity networks [Hec91].”
Bayesian Artificial Intelligence (2004, methodology): “One method for eliciting local structure is “elicitation by partition” [102, 90, 181].”
Toward Normative Expert Systems: Part II Probability-Based Representations for Efficient Knowledge Acquisition and Inference (1992, methodology): “To construct Pathfinder, we created SimNet, an implementation of the belief-network, similaritynetwork, and partition representations on the Macintosh computer [5].”
From certainty factors to belief networks (1992, methodology): “The belief network for Pathfinder was constructed with the aid of a similarity network, an extension of the belief-network representation that permits the incremental construction of extremely large belief networks from cognitively manageable subproblems that involve the comparison of two diseases a”
An evaluation of explanations of probabilistic inference. (1992, background): “Such a theoretical foundation has been demonstrated to improve the accuracy and consistency of systems' conclusions (Heckerman and Horvitz, 1987; Heckerman, 1990a), which may ultimately affect our ability to obtain user confidence in the system's conclusions.”