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» On the Network Complexity of Selection
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CSB
2002
IEEE
169views Bioinformatics» more  CSB 2002»
15 years 12 months ago
Bayesian Network and Nonparametric Heteroscedastic Regression for Nonlinear Modeling of Genetic Network
We propose a new statistical method for constructing a genetic network from microarray gene expression data by using a Bayesian network. An essential point of Bayesian network con...
Seiya Imoto, SunYong Kim, Takao Goto, Sachiyo Abur...
COSIT
2007
Springer
89views GIS» more  COSIT 2007»
16 years 1 months ago
Specifying Essential Features of Street Networks
In order to apply advanced high-level concepts for transportation networks, like hypergraphs, multi-level wayfinding and traffic forecasting, to commercially available street netwo...
Simon Scheider, Daniel Schulz
DSN
2005
IEEE
15 years 8 months ago
A Spatial Fluid-Based Framework to Analyze Large-Scale Wireless Sensor Networks
The behavior of large-scale wireless sensor networks has been shown to be surprisingly complex and difficult to analyze, both by empirical experiment and simulation. In this pape...
Marco Gribaudo, Carla-Fabiana Chiasserini, Rossano...
AINA
2010
IEEE
15 years 5 months ago
Compensation of Sensors Nonlinearity with Neural Networks
—This paper describes a method of linearizing the nonlinear characteristics of many sensors using an embedded neural network. The proposed method allows for complex neural networ...
Nicholas J. Cotton, Bogdan M. Wilamowski
EWMF
2005
Springer
16 years 12 days ago
Information Retrieval in Trust-Enhanced Document Networks
Abstract. To fight the problem of information overload in huge information sources like large document repositories, e. g. citeseer, or internet websites you need a selection crit...
Klaus Stein, Claudia Hess