Hierarchical Temporal Memory: Machine learning, Jeff Hawkins, Algorithm, Neocortex, Bayesian network, Memory-prediction framework, On Intelligence, Bionics, Tomaso Poggio -
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Hierarchical temporal memory is a machine learning model developed by Jeff Hawkins and Dileep George of Numenta, Inc. that models some of the structural and algorithmic properties of the neocortex using an approach somewhat similar to Bayesian networks. HTM model is based on the memory-prediction theory of brain function described by Jeff Hawkins in his book On Intelligence. HTMs are claimed to be biomimeti ... Full description
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More Information
| Publisher | OmniScriptum |
|---|---|
| Release year | 2026 |
| Cover type | Softcover |
| EAN | 9786130677572 |