115 search results - page 5 / 23 » Bayesian Learning of Loglinear Models for Neural Connectivit... |
NIPS
2001
15 years 1 months ago
2001
Statistical learning and probabilistic inference techniques are used to infer the hand position of a subject from multi-electrode recordings of neural activity in motor cortex. Fi...
NN
2002
Springer
14 years 11 months ago
2002
Springer
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
JETAI
1998
14 years 11 months ago
1998
Graphical structures such as Bayesian networks or Markov networks are very useful tools for representing irrelevance or independency relationships, and they may be used to e cientl...
116
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JMLR
2010
14 years 6 months ago
2010
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
107
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NN
2000
Springer
14 years 11 months ago
2000
Springer
A neural network model that can simulate the learning of some simple proportional analogies is presented. These analogies include, for example, (a) red-square:red-circle yellow-sq...