280 search results - page 7 / 56 » Movement Prediction Using Bayesian Learning for Neural Netwo... |
136
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DCC
2010
IEEE
15 years 4 months ago
2010
IEEE
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
155
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ICANN
2001
Springer
15 years 10 months ago
2001
Springer
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
156
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NN
1997
Springer
15 years 10 months ago
1997
Springer
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
180
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NIPS
2008
15 years 7 months ago
2008
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
183
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ICANN
2010
Springer
15 years 4 months ago
2010
Springer
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...