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NIPS
2000
15 years 8 months ago
A Neural Probabilistic Language Model
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Yoshua Bengio, Réjean Ducharme, Pascal Vinc...
NIPS
1994
15 years 8 months ago
Using a neural net to instantiate a deformable model
Deformable models are an attractive approach to recognizing nonrigid objects which have considerable within class variability. However, there are severe search problems associated...
Christopher K. I. Williams, Michael Revow, Geoffre...
211
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ECAL
1999
Springer
15 years 11 months ago
Evolution of Neural Controllers with Adaptive Synapses and Compact Genetic Encoding
Abstract. This paper is concerned with arti cial evolution of neurocontrollers with adaptive synapses for autonomous mobile robots. The method consists of encoding on the genotype ...
Dario Floreano, Joseba Urzelai
IJCNN
2006
IEEE
16 years 21 days ago
Reconstruction of Gene Regulatory Networks from Temporal Microarray Data Using Pattern Recognition Techniques
- Gene regulatory networks allow us to study and understand genes’ roles in biological processes. Among others, regulatory networks help to identify pathway initiator genes and t...
Azhar Salim, Faramarz Valafar
NN
1997
Springer
174views Neural Networks» more  NN 1997»
15 years 10 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani