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» Learning a Generative Model for Structural Representations
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NN
2008
Springer
169views Neural Networks» more  NN 2008»
13 years 7 months ago
Modeling a flexible representation machinery of human concept learning
dely acknowledged that categorically organized abstract knowledge plays a significant role in high-order human cognition. Yet, there are many unknown issues about the nature of ho...
Toshihiko Matsuka, Yasuaki Sakamoto, Arieta Chouch...
BMCBI
2006
101views more  BMCBI 2006»
13 years 7 months ago
SynTReN: a generator of synthetic gene expression data for design and analysis of structure learning algorithms
Background: The development of algorithms to infer the structure of gene regulatory networks based on expression data is an important subject in bioinformatics research. Validatio...
Tim Van den Bulcke, Koen Van Leemput, Bart Naudts,...
JCC
2008
92views more  JCC 2008»
13 years 7 months ago
Fast procedure for reconstruction of full-atom protein models from reduced representations
: We introduce PULCHRA, a fast and robust method for the reconstruction of full-atom protein models starting from a reduced protein representation. The algorithm is particularly su...
Piotr Rotkiewicz, Jeffrey Skolnick
SCVMA
2004
Springer
14 years 25 days ago
A Generative Model of Dense Optical Flow in Layers
We introduce a generative model of dense flow fields within a layered representation of 3-dimensional scenes. Using probabilistic inference and learning techniques (namely, varia...
Anitha Kannan, Brendan J. Frey, Nebojsa Jojic
ICML
2008
IEEE
14 years 8 months ago
Extracting and composing robust features with denoising autoencoders
Previous work has shown that the difficulties in learning deep generative or discriminative models can be overcome by an initial unsupervised learning step that maps inputs to use...
Pascal Vincent, Hugo Larochelle, Yoshua Bengio, Pi...