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Lauritzen and Spiegelhalter: local probability computation in graphical expert systems

Developed exact local probability propagation for sparse graphical expert systems by transforming the graph and transferring information among local representations.

What is recorded here?

Developed exact local probability propagation for sparse graphical expert systems by transforming the graph and transferring information among local representations.

Source-linked catalogue note. A detailed explanatory guide has not yet been prepared for this entry.

Scientific scope

The record is the exact two-author 1988 JRSS B paper and its sparse-network propagation framework. It does not absorb all belief-propagation variants, later junction-tree software or every probabilistic graphical model.

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People and systems

Steffen L. Lauritzen; David J. Spiegelhalter

The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.

Research locations and affiliations

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Documented countries / regions: Denmark, United Kingdom

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English catalogue narrative

Lauritzen and Spiegelhalter: local probability computation in graphical expert systems

Developed exact local probability propagation for sparse graphical expert systems by transforming the graph and transferring information among local representations.

Scientific scope

The record is the exact two-author 1988 JRSS B paper and its sparse-network propagation framework. It does not absorb all belief-propagation variants, later junction-tree software or every probabilistic graphical model.

Reading status

This is a source-linked WRS catalogue note. A full explanatory guide and independent scientific reconstruction have not been completed for this entry. Read the identified original work for its complete narrative and arguments.

People and systems

Steffen L. Lauritzen; David J. Spiegelhalter

The named authors contributed to this scoped work; individual effort shares and later applications are not assigned by the byline.

Original sources