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» Information complexity of neural networks
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103
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AI50
2006
15 years 3 months ago
What Can AI Get from Neuroscience?
The human brain is the best example of intelligence known, with unsurpassed ability for complex, real-time interaction with a dynamic world. AI researchers trying to imitate its re...
Steve M. Potter
AMC
2008
78views more  AMC 2008»
14 years 12 months ago
Information processing in complex networks: Graph entropy and information functionals
This paper introduces a general framework for defining the entropy of a graph. Our definition is based on a local information graph and on information functionals derived from the...
Matthias Dehmer
88
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APPINF
2003
15 years 1 months ago
Preventing Computational Chaos in Asynchronous Neural Networks
One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...
Jacob Barhen, Vladimir Protopopescu
ICANN
2007
Springer
15 years 6 months ago
Neural Mechanisms for Mid-Level Optical Flow Pattern Detection
This paper describes a new model for extracting large-field optical flow patterns to generate distributed representations of neural activation to control complex visual tasks such ...
Stefan Ringbauer, Pierre Bayerl, Heiko Neumann
BMCBI
2008
138views more  BMCBI 2008»
14 years 12 months ago
Using neural networks and evolutionary information in decoy discrimination for protein tertiary structure prediction
Background: We present a novel method of protein fold decoy discrimination using machine learning, more specifically using neural networks. Here, decoy discrimination is represent...
Ching-Wai Tan, David T. Jones