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» Neural networks for computational neuroscience
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APIN
1999
107views more  APIN 1999»
15 years 6 months ago
Massively Parallel Probabilistic Reasoning with Boltzmann Machines
We present a method for mapping a given Bayesian network to a Boltzmann machine architecture, in the sense that the the updating process of the resulting Boltzmann machine model pr...
Petri Myllymäki
IJCNN
2008
IEEE
16 years 26 days ago
Dynamic logic of phenomena and cognition
—Modeling of complex phenomena such as the mind presents tremendous computational complexity challenges. The neural modeling fields theory (NMF) addresses these challenges in a n...
Boris Kovalerchuk, Leonid I. Perlovsky
GIS
2009
ACM
15 years 10 months ago
Dynamic network data exploration through semi-supervised functional embedding
The paper presents a framework for semi-supervised nonlinear embedding methods useful for exploratory analysis and visualization of spatio-temporal network data. The method provid...
Alexei Pozdnoukhov
GECCO
2010
Springer
183views Optimization» more  GECCO 2010»
15 years 11 months ago
Neuroevolution of mobile ad hoc networks
This paper describes a study of the evolution of distributed behavior, specifically the control of agents in a mobile ad hoc network, using neuroevolution. In neuroevolution, a p...
David B. Knoester, Heather Goldsby, Philip K. McKi...
IJON
2006
76views more  IJON 2006»
15 years 6 months ago
Evolving networks of integrate-and-fire neurons
This paper addresses the following question: ``What neural circuits can emulate the monosynaptic correlogram generated by a direct connection between two neurons?'' The ...
Francisco J. Veredas, Francisco J. Vico, Jos&eacut...