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    » Using Goal-Models to Analyze Variability
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    TRS
    2008
    136views Artificial Intelligence» more  TRS 2008»
    The Neurophysiological Bases of Cognitive Computation Using Rough Set Theory
    13 years 8 months ago
    The Neurophysiological Bases of Cognitive Computation Using Rough Set Theory
    Download  www.umassmed.edu
    A popular view is that the brain works in a similar way to a digital computer or a Universal Turing Machine by processing symbols. Psychophysical experiments and our amazing capabi...
    Andrzej W. Przybyszewski
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    VALUETOOLS
    2006
    ACM
    164views Hardware» more  VALUETOOLS 2006»
    Analysis of Markov reward models using zero-suppressed multi-terminal BDDs
    14 years 2 months ago
    Analysis of Markov reward models using zero-suppressed multi-terminal BDDs
    Download  www.unibw.de
    High-level stochastic description methods such as stochastic Petri nets, stochastic UML statecharts etc., together with specifications of performance variables (PVs), enable a co...
    Kai Lampka, Markus Siegle
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    BMCBI
    2004
    165views more  BMCBI 2004»
    Analysis of oligonucleotide array experiments with repeated measures using mixed models
    13 years 8 months ago
    Analysis of oligonucleotide array experiments with repeated measures using mixed models
    Download  www.biomedcentral.com
    Background: Two or more factor mixed factorial experiments are becoming increasingly common in microarray data analysis. In this case study, the two factors are presence (Patients...
    Hao Li, Constance L. Wood, Thomas V. Getchell, Mar...
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    ETVC
    2008
    251views Applied Computing» more  ETVC 2008»
    Statistical Computing on Manifolds: From Riemannian Geometry to Computational Anatomy
    13 years 10 months ago
    Statistical Computing on Manifolds: From Riemannian Geometry to Computational Anatomy
    Download  www-sop.inria.fr
    Computational anatomy is an emerging discipline that aims at analyzing and modeling the individual anatomy of organs and their biological variability across a population. The goal ...
    Xavier Pennec
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    BMCBI
    2010
    135views more  BMCBI 2010»
    Simple and flexible classification of gene expression microarrays via Swirls and Ripples
    13 years 9 months ago
    Simple and flexible classification of gene expression microarrays via Swirls and Ripples
    Download  www.biomedcentral.com
    Background: A simple classification rule with few genes and parameters is desirable when applying a classification rule to new data. One popular simple classification rule, diagon...
    Stuart G. Baker
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