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    ICANN
    2007
    Springer
    165views Neural Networks» more  ICANN 2007»
    Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping
    14 years 28 days ago
    Neural Network Approach for Mass Spectrometry Prediction by Peptide Prototyping
    Download  bio.informatik.uni-jena.de
    In todays bioinformatics, Mass spectrometry (MS) is the key technique for the identification of proteins. A prediction of spectrum peak intensities from pre computed molecular feat...
    Alexandra Scherbart, Wiebke Timm, Sebastian Bö...
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    NIPS
    2008
    179views Information Technology» more  NIPS 2008»
    Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks
    13 years 10 months ago
    Offline Handwriting Recognition with Multidimensional Recurrent Neural Networks
    Download  www.idsia.ch
    Offline handwriting recognition--the transcription of images of handwritten text--is an interesting task, in that it combines computer vision with sequence learning. In most syste...
    Alex Graves, Jürgen Schmidhuber
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    IJPRAI
    1998
    100views more  IJPRAI 1998»
    Obtaining The Correspondence between Bayesian and Neural Networks
    13 years 8 months ago
    Obtaining The Correspondence between Bayesian and Neural Networks
    Download  homepages.inf.ed.ac.uk
    We present in this paper a novel method for eliciting the conditional probability matrices needed for a Bayesian network with the help of a neural network. We demonstrate how we c...
    Athena Stassopoulou, Maria Petrou
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    NIPS
    2003
    139views Information Technology» more  NIPS 2003»
    Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
    13 years 10 months ago
    Maximum Likelihood Estimation of a Stochastic Integrate-and-Fire Neural Model
    Download  pillowlab.cps.utexas.edu
    Recent work has examined the estimation of models of stimulus-driven neural activity in which some linear filtering process is followed by a nonlinear, probabilistic spiking stag...
    Jonathan Pillow, Liam Paninski, Eero P. Simoncelli
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    IEEEPACT
    2005
    IEEE
    92views Distributed And Parallel Com...» more  IEEEPACT 2005»
    A Simple Divide-and-Conquer Approach for Neural-Class Branch Prediction
    14 years 2 months ago
    A Simple Divide-and-Conquer Approach for Neural-Class Branch Prediction
    Download  www.cc.gatech.edu
    The continual demand for greater performance and growing concerns about the power consumption in highperformance microprocessors make the branch predictor a critical component of ...
    Gabriel H. Loh
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