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NIPS
2008
13 years 9 months ago
On Computational Power and the Order-Chaos Phase Transition in Reservoir Computing
Randomly connected recurrent neural circuits have proven to be very powerful models for online computations when a trained memoryless readout function is appended. Such Reservoir ...
Benjamin Schrauwen, Lars Buesing, Robert A. Legens...
CEC
2008
IEEE
14 years 2 months ago
Neuro-evolving maintain-station behavior for realistically simulated boats
— We evolve a neural network controller for a boat that learns to maintain a given bearing and range with respect to a moving target in the Lagoon 3D game environment. Simulating...
Nathan A. Penrod, David Carr, Sushil J. Louis, Bob...
CORR
2002
Springer
106views Education» more  CORR 2002»
13 years 7 months ago
On model selection and the disability of neural networks to decompose tasks
A neural network with fixed topology can be regarded as a parametrization of functions, which decides on the correlations between functional variations when parameters are adapted...
Marc Toussaint
IJON
2006
67views more  IJON 2006»
13 years 7 months ago
Robust persistent activity in neural fields with asymmetric connectivity
Modeling studies have shown that recurrent interactions within neural networks are capable of self-sustaining non-uniform activity profiles. These patterns are thought to be the n...
Cláudia Horta, Wolfram Erlhagen
CLEIEJ
2007
152views more  CLEIEJ 2007»
13 years 7 months ago
Gene Expression Analysis using Markov Chains extracted from RNNs
Abstract. This paper present a new approach for the analysis of gene expression, by extracting a Markov Chain from trained Recurrent Neural Networks (RNNs). A lot of microarray dat...
Igor Lorenzato Almeida, Denise Regina Pechmann Sim...