115 search results - page 8 / 23 » Bayesian Learning of Loglinear Models for Neural Connectivit... |
ML
2002
ACM
14 years 11 months ago
2002
ACM
When simple parametric models such as linear regression fail to adequately approximate a relationship across an entire set of data, an alternative may be to consider a partition o...
98
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NIPS
1997
15 years 1 months ago
1997
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
106
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FUIN
2008
14 years 10 months ago
2008
Causal relations are present in many application domains. Causal Probabilistic Logic (CP-logic) is a probabilistic modeling language that is especially designed to express such rel...
126
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ICMCS
2008
IEEE
15 years 6 months ago
2008
IEEE
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
102
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COGSCI
2007
14 years 11 months ago
2007
: Modularity in the human brain remains a controversial issue, with disagreement over the nature of the modules that exist, and why, when and how they emerge. It is a natural assum...