Hasil Pencarian - Wulfram eGerstner

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  1. 1
    From Hebb rules to Spike-Timing-Dependent Plasticity: a personal account

    From Hebb rules to Spike-Timing-Dependent Plasticity: a personal account oleh Wulfram eGerstner

    Diterbitkan 2010-12-01
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  2. 2
    Limits to high-speed simulations of spiking neural networks using general-purpose computers

    Limits to high-speed simulations of spiking neural networks using general-purpose computers oleh Friedemann eZenke, Friedemann eZenke, Wulfram eGerstner, Wulfram eGerstner

    Diterbitkan 2014-09-01
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  3. 3
    Stochastic Variational Learning in Recurrent Spiking Networks

    Stochastic Variational Learning in Recurrent Spiking Networks oleh Danilo eJimenez Rezende, Danilo eJimenez Rezende, Wulfram eGerstner, Wulfram eGerstner

    Diterbitkan 2014-04-01
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  4. 4
    Neuromodulated Spike-Timing-Dependent Plasticity and Theory of Three-Factor Learning Rules

    Neuromodulated Spike-Timing-Dependent Plasticity and Theory of Three-Factor Learning Rules oleh Wulfram eGerstner, Nicolas eFremaux

    Diterbitkan 2016-01-01
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  5. 5
    Spike-timing prediction in cortical neurons with active dendrites

    Spike-timing prediction in cortical neurons with active dendrites oleh Richard eNaud, Brice eBathellier, Wulfram eGerstner

    Diterbitkan 2014-08-01
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  6. 6
    Spike-timing-dependent plasticity: a comprehensive overview

    Spike-timing-dependent plasticity: a comprehensive overview oleh Henry eMarkram, Wulfram eGerstner, Per Jesper eSjöström

    Diterbitkan 2012-07-01
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  7. 7
    A history of spike-timing-dependent plasticity

    A history of spike-timing-dependent plasticity oleh Henry eMarkram, Wulfram eGerstner, Per Jesper eSjöström, Per Jesper eSjöström

    Diterbitkan 2011-08-01
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  8. 8
    Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate

    Reward-based learning under hardware constraints - Using a RISC processor embedded in a neuromorphic substrate oleh Simon eFriedmann, Nicolas eFrémaux, Johannes eSchemmel, Wulfram eGerstner, Karlheinz eMeier

    Diterbitkan 2013-09-01
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  9. 9
    A model of synaptic reconsolidation

    A model of synaptic reconsolidation oleh David B. Kastner, David B. Kastner, Tilo eSchwalger, Lorric eZiegler, Wulfram eGerstner

    Diterbitkan 2016-05-01
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  10. 10
    Inference of neuronal network spike dynamics and topology from calcium imaging data

    Inference of neuronal network spike dynamics and topology from calcium imaging data oleh Henry eLütcke, Felipe eGerhard, Friedemann eZenke, Wulfram eGerstner, Fritjof eHelmchen, Fritjof eHelmchen

    Diterbitkan 2013-12-01
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  11. 11
    Extraction of network topology from multi-electrode recordings: Is there a small-world effect?

    Extraction of network topology from multi-electrode recordings: Is there a small-world effect? oleh Felipe eGerhard, Gordon ePipa, Gordon ePipa, Gordon ePipa, Bruss eLima, Sergio eNeuenschwander, Wulfram eGerstner

    Diterbitkan 2011-02-01
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