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ICANN
2010
Springer
3 years 6 months ago
Learning in a Unitary Coherent Hippocampus
Abstract. A previous paper [2] presented a model (UCPF-HC) of the hippocampus as a unitary coherent particle filter, which combines the classical hippocampal roles of associative m...
Charles W. Fox, Tony J. Prescott
ICANN
2010
Springer
3 years 6 months ago
Dynamics and Function of a CA1 Model of the Hippocampus during Theta and Ripples
The hippocampus is known to be involved in spatial learning in rats. Spatial learning involves the encoding and replay of temporally sequenced spatial information. Temporally seque...
Vassilis Cutsuridis, Michael E. Hasselmo
ICANN
2010
Springer
3 years 6 months ago
The Support Feature Machine for Classifying with the Least Number of Features
We propose the so-called Support Feature Machine (SFM) as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separating hyperplan...
Sascha Klement, Thomas Martinetz
ANNS
2010
3 years 6 months ago
A Software Framework for Mapping Neural Networks to a Wafer-scale Neuromorphic Hardware System
In this contribution we will provide the reader with outcomes of the development of a novel software framework for an unique wafer-scale neuromordware system. The hardware system i...
Matthias Ehrlich, Karsten Wendt, Lukas Zühl, ...
NN
2010
Springer
3 years 7 months ago
Synaptic rewiring for topographic mapping and receptive field development
Simeon A. Bamford, Alan F. Murray, David J. Willsh...
NN
2010
Springer
185views Neural Networks» more  NN 2010»
3 years 7 months ago
Learning to imitate stochastic time series in a compositional way by chaos
This study shows that a mixture of RNN experts model can acquire the ability to generate sequences that are combination of multiple primitive patterns by means of self-organizing ...
Jun Namikawa, Jun Tani
NN
2010
Springer
121views Neural Networks» more  NN 2010»
3 years 7 months ago
Neural network model for completing occluded contours
— This paper proposes a neural network model capable of completing partly occluded contours. The model is a hierarchical multi-layered network. Using the responses of bend-extrac...
Kunihiko Fukushima
NN
2010
Springer
100views Neural Networks» more  NN 2010»
3 years 7 months ago
Parameter-exploring policy gradients
We present a model-free reinforcement learning method for partially observable Markov decision problems. Our method estimates a likelihood gradient by sampling directly in paramet...
Frank Sehnke, Christian Osendorfer, Thomas Rü...
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