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» Neural networks for computational neuroscience
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CIMCA
2005
IEEE
15 years 11 months ago
Hybrid Neural Networks for Immunoinformatics
Hybrid set of optimally trained feed-forward, Hopfield and Elman neural networks were used as computational tools and were applied to immunoinformatics. These neural networks ena...
Khrizel B. Solano, Tolja Djekovic, Mohamed Zohdy
ARTMED
2002
121views more  ARTMED 2002»
15 years 6 months ago
An evolutionary artificial neural networks approach for breast cancer diagnosis
This paper presents an evolutionary artificial neural network approach based on the pareto differential evolution algorithm augmented with local search for the prediction of breas...
Hussein A. Abbass
TNN
2008
177views more  TNN 2008»
15 years 6 months ago
Adaptive Importance Sampling to Accelerate Training of a Neural Probabilistic Language Model
Previous work on statistical language modeling has shown that it is possible to train a feed-forward neural network to approximate probabilities over sequences of words, resulting...
Yoshua Bengio, Jean-Sébastien Senecal
IJON
2010
127views more  IJON 2010»
15 years 4 months ago
Oscillation in a network model of neocortex
A basic understanding of the relationship between activity of individual neurons and macroscopic electrical activity of local field potentials or electroencephalogram (EEG) may pro...
Jennifer Dwyer, Hyong Lee, Amber Martell, Rick L. ...
IJCAI
2001
15 years 7 months ago
Genetic Algorithm based Selective Neural Network Ensemble
Neural network ensemble is a learning paradigm where several neural networks are jointly used to solve a problem. In this paper, the relationship between the generalization abilit...
Zhi-Hua Zhou, Jianxin Wu, Yuan Jiang, Shifu Chen