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» Reconstruction for Models on Random Graphs
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UAI
2004
15 years 1 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
14 years 12 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 6 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
INFOCOM
2007
IEEE
15 years 6 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 6 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