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Self-generated Off-line Memory Reprocessing Strongly Improves Generalization in a Hierarchical Recurrent Neural Network
Jitsev, J. (Corresponding Author) FZJ *
2014
Springer International Publishing
Cham
ISBN: 978-3-319-11179-7, 978-3-319-11179-7 (electronic)
2014 24th International Conference on Artificial Neural Networks , ICANN 2014 , Hamburg Hamburg , Germany , 15 Sep 2014 - 19 Sep 20142014-09-15 2014-09-19
Cham : Springer International Publishing, Lecture Notes in Computer Science 8681 , 659 - 666 (2014 ) [10.1007/978-3-319-11179-7_83 ] 2014
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Please use a persistent id in citations: doi:10.1007/978-3-319-11179-7_83
Contributing Institute(s):
Computational and Systems Neuroscience (INM-6) Theoretical Neuroscience (IAS-6)
Research Program(s):
574 - Theory, modelling and simulation (POF3-574) (POF3-574) 89574 - Theory, modelling and simulation (POF2-89574) (POF2-89574) 331 - Signalling Pathways and Mechanisms in the Nervous System (POF2-331) (POF2-331) SMHB - Supercomputing and Modelling for the Human Brain (HGF-SMHB-2013-2017) (HGF-SMHB-2013-2017)
Appears in the scientific report
2014
Database coverage: JCR ; Nationallizenz
; SCOPUS ; Thomson Reuters Master Journal List ; Web of Science Core Collection