115 search results - page 4 / 23 » Bayesian Learning of Loglinear Models for Neural Connectivit... |
70
Voted
CONNECTION
2004
14 years 9 months ago
2004
While humans forget gradually, highly distributed connectionist networks forget catastrophically: newly learned information often completely erases previously learned information. ...
IJON
2006
14 years 9 months ago
2006
The neurons in the mammalian visual cortex are arranged in columnar structures, and the synaptic contacts of the pyramidal neurons in layer II/III are clustered into patches that ...
66
Voted
ESANN
2000
14 years 11 months ago
2000
: Recurrent neural networks possess interesting universal approximation capabilities, making them good candidates for time series modeling. Unfortunately, long term dependencies ar...
CONNECTION
2006
14 years 9 months ago
2006
Models of associative memory usually have full connectivity or if diluted, random symmetric connectivity. In contrast, biological neural systems have predominantly local, non-symm...
ECML
2003
Springer
15 years 2 months ago
2003
Springer
Abstract. This paper studies the properties and performance of models for estimating local probability distributions which are used as components of larger probabilistic systems â€...