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» Reconstruction for Models on Random Graphs
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UAI
2004
15 years 3 months ago
Convolutional Factor Graphs as Probabilistic Models
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...
Yongyi Mao, Frank R. Kschischang, Brendan J. Frey
CAD
2007
Springer
15 years 1 months ago
Detection of closed sharp edges in point clouds using normal estimation and graph theory
The reconstruction of a surface model from a point cloud is an important task in the reverse engineering of industrial parts. We aim at constructing a curve network on the point c...
Kris Demarsin, Denis Vanderstraeten, Tim Volodine,...
SAC
2010
ACM
15 years 8 months ago
Estimating node similarity from co-citation in a spatial graph model
Co-citation (number of nodes linking to both of a given pair of nodes) is often used heuristically to judge similarity between nodes in a complex network. We investigate the relat...
Jeannette Janssen, Pawel Pralat, Rory Wilson
132
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INFOCOM
2007
IEEE
15 years 8 months ago
A Graph-Based Model for Disconnected Ad Hoc Networks
— Recently, research on disconnected networks has been fostered by several studies on delay-tolerant networks, which are designed in order to sustain disconnected operations. We ...
Francesco De Pellegrini, Daniele Miorandi, Iacopo ...
JMLR
2011
145views more  JMLR 2011»
14 years 9 months ago
Cumulative Distribution Networks and the Derivative-sum-product Algorithm: Models and Inference for Cumulative Distribution Func
We present a class of graphical models for directly representing the joint cumulative distribution function (CDF) of many random variables, called cumulative distribution networks...
Jim C. Huang, Brendan J. Frey