Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning.
about
Neuromodulated Spike-Timing-Dependent Plasticity, and Theory of Three-Factor Learning RulesSpike-Based Bayesian-Hebbian Learning of Temporal SequencesTraining spiking neural models using artificial bee colony.Functional network reorganization in motor cortex can be explained by reward-modulated Hebbian learning.A reward-modulated hebbian learning rule can explain experimentally observed network reorganization in a brain control task.Realignment of interaural cortical maps in asymmetric hearing loss.Spike-based reinforcement learning in continuous state and action space: when policy gradient methods failA learning theory for reward-modulated spike-timing-dependent plasticity with application to biofeedbackTag-trigger-consolidation: a model of early and late long-term-potentiation and depressionReinforcement learning on slow features of high-dimensional input streamsA Model of Fast Hebbian Spike Latency NormalizationDemocratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations.Spatio-temporal credit assignment in neuronal population learning.Supervised learning with decision margins in pools of spiking neuronsThe chronotron: a neuron that learns to fire temporally precise spike patterns.Spike-based decision learning of Nash equilibria in two-player gamesCoding and decoding with adapting neurons: a population approach to the peri-stimulus time histogram.Anti-hebbian spike-timing-dependent plasticity and adaptive sensory processing.Synaptic consolidation: an approach to long-term learningReinforcement learning using a continuous time actor-critic framework with spiking neurons.Bayesian computation emerges in generic cortical microcircuits through spike-timing-dependent plasticityChoice-correlated activity fluctuations underlie learning of neuronal category representationHuman and machine learning in non-Markovian decision makingA biophysically-based neuromorphic model of spike rate- and timing-dependent plasticity.A Reward-Maximizing Spiking Neuron as a Bounded Rational Decision Maker.Somato-dendritic Synaptic Plasticity and Error-backpropagation in Active Dendrites.Learning of Precise Spike Times with Homeostatic Membrane Potential Dependent Synaptic Plasticity.Gradient estimation in dendritic reinforcement learningProspective Coding by Spiking Neurons.Supervised Learning in Spiking Neural Networks for Precise Temporal EncodingChanging the responses of cortical neurons from sub- to suprathreshold using single spikes in vivo.Building functional networks of spiking model neurons.Mathematical properties of neuronal TD-rules and differential Hebbian learning: a comparisonPhenomenological models of synaptic plasticity based on spike timing.Stochastic variational learning in recurrent spiking networks.Coexistence of reward and unsupervised learning during the operant conditioning of neural firing rates.Learning Probabilistic Inference through Spike-Timing-Dependent Plasticity.Motoneuron membrane potentials follow a time inhomogeneous jump diffusion process.Learning Spatiotemporally Encoded Pattern Transformations in Structured Spiking Neural Networks.STDP in Adaptive Neurons Gives Close-To-Optimal Information Transmission.
P2860
Q26772828-56E35FD6-9639-4A8D-9183-73AF742DA00FQ28552341-E4331F3D-7121-462E-85D6-C7E41FC4E352Q30418190-4094BDFA-9666-4739-8ACF-39B30C33A769Q30429179-9FA715C3-8869-4762-A0B4-77A287C2F2A1Q30478447-7E996728-2FD8-4965-B839-AD286BDC473AQ30485108-8271BBBE-23FA-4CD0-A656-3510C1A708F2Q30972868-6ED5A25A-4C90-4DF2-96F8-81BE646DBD5AQ33375018-D27C408B-E85C-4EE1-917D-241661F6FDC7Q33396203-A308A075-EA95-401F-95AF-8370066AB351Q33680656-26C95E2A-203A-46D0-9E3D-40A314B439A4Q33683546-08AFB6F4-2868-4F76-B245-752ADA932FA2Q33900113-4CE11F4C-1AB0-4B1F-874A-81D683B8D420Q33954343-3D9A9349-BA13-495F-A85A-333FE0632028Q34157379-358522EC-83F7-4840-BC81-85AD0DE23493Q34373928-47A3092E-751A-4692-A925-0A488F1DE26CQ34426365-59D70028-C379-43DA-BAF4-D04D9E81C249Q34440608-2676B627-CB85-4B3A-A68A-72B3AB953CB3Q34479898-A3815704-5EA8-4F00-880A-60C790708BA9Q34652541-ABF44A28-7D1B-4119-B243-0E0DCB716178Q34671773-0567884E-5861-467D-A1C4-9DDBB8D83D1FQ34697786-6391679D-7178-4C9C-A458-C930F18B70D9Q35244988-76AE22AE-6B14-40DD-9F43-08281A358611Q35515822-F3C1A4CF-E83E-4F9C-9F4C-5FBE4190154FQ35621127-C190F430-E142-47FE-BE8D-32A27B46423AQ35665009-5B1308B4-6890-4EF4-B98C-750697B34707Q35913608-6DE896D1-B065-4609-885B-8D47614AA327Q35930453-ADFBEB2B-2260-4F08-BD2C-1F2C1B1CBBF1Q36003463-4F1E9359-7AE0-4C3A-BBC7-79B269A11FDFQ36060906-112D6949-C4B9-4B2C-AE57-4AFAB54EA499Q36105643-730A98A4-A416-478C-A544-45E78FCF3DBFQ36554900-3DBECE46-C1DC-4A86-9FA0-B5F9DC5B28B3Q37055642-0547465C-BEFC-4E7E-A895-821F11E55BF8Q37057321-531964D0-599C-4486-9281-B5F2B6E68DFDQ37168294-DEFED42D-5948-4399-A05A-22B15047BE29Q37697641-16655581-A808-4CB0-BA7F-7078D2EE3331Q39261265-3A982FAF-096D-4B53-A202-7629A4304C8DQ39599319-14382EA5-AFD7-4613-B686-E8E5D327BA3BQ39648426-E5A4C23E-DED5-4E70-A000-4EFC18D87559Q40398877-752D82B6-BFD9-4AA4-879E-9B7C3D424E72Q41155927-E526244F-95C7-49C1-A172-17608DE25A06
P2860
Optimal spike-timing-dependent plasticity for precise action potential firing in supervised learning.
description
2006 nî lūn-bûn
@nan
2006年の論文
@ja
2006年学术文章
@wuu
2006年学术文章
@zh
2006年学术文章
@zh-cn
2006年学术文章
@zh-hans
2006年学术文章
@zh-my
2006年学术文章
@zh-sg
2006年學術文章
@yue
2006年學術文章
@zh-hant
name
Optimal spike-timing-dependent ...... firing in supervised learning.
@en
Optimal spike-timing-dependent ...... firing in supervised learning.
@nl
type
label
Optimal spike-timing-dependent ...... firing in supervised learning.
@en
Optimal spike-timing-dependent ...... firing in supervised learning.
@nl
prefLabel
Optimal spike-timing-dependent ...... firing in supervised learning.
@en
Optimal spike-timing-dependent ...... firing in supervised learning.
@nl
P2860
P50
P1433
P1476
Optimal spike-timing-dependent ...... firing in supervised learning.
@en
P2093
David Barber
P2860
P304
P356
10.1162/NECO.2006.18.6.1318
P577
2006-06-01T00:00:00Z