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» Learning a Generative Model for Structural Representations
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ICANN
2005
Springer
15 years 8 months ago
Accurate and Robust Image Superresolution by Neural Processing of Local Image Representations
Image superresolution involves the processing of an image sequence to generate a still image with higher resolution. Classical approaches, such as bayesian MAP methods, require ite...
Carlos Miravet, Francisco de Borja Rodrígue...
CORR
2006
Springer
102views Education» more  CORR 2006»
15 years 2 months ago
Structural Inference of Hierarchies in Networks
One property of networks that has received comparatively little attention is hierarchy, i.e., the property of having vertices that cluster together in groups, which then join to f...
Aaron Clauset, Cristopher Moore, M. E. J. Newman
ICML
2005
IEEE
16 years 3 months ago
Efficient discriminative learning of Bayesian network classifier via boosted augmented naive Bayes
The use of Bayesian networks for classification problems has received significant recent attention. Although computationally efficient, the standard maximum likelihood learning me...
Yushi Jing, Vladimir Pavlovic, James M. Rehg
IJON
2007
88views more  IJON 2007»
15 years 2 months ago
Self-organisation can generate the discontinuities in the somatosensory map
The primary somatosensory cortex contains a topographic map of the body surface, with two notable discontinuities — the representation of the face is next to that of the hands, ...
Tom Stafford, Stuart P. Wilson
TNN
1998
123views more  TNN 1998»
15 years 2 months ago
A general framework for adaptive processing of data structures
—A structured organization of information is typically required by symbolic processing. On the other hand, most connectionist models assume that data are organized according to r...
Paolo Frasconi, Marco Gori, Alessandro Sperduti