STDP installs in Winner-Take-All circuits an online approximation to hidden Markov model learning
about
Distributed Bayesian Computation and Self-Organized Learning in Sheets of Spiking Neurons with Local Lateral InhibitionSpike-Based Bayesian-Hebbian Learning of Temporal SequencesToward an Integration of Deep Learning and NeuroscienceA framework for plasticity implementation on the SpiNNaker neural architecture.Spatiotemporal features for asynchronous event-based data.Ensembles of spiking neurons with noise support optimal probabilistic inference in a dynamically changing environment.Racing to learn: statistical inference and learning in a single spiking neuron with adaptive kernels.Dynamics of multistable states during ongoing and evoked cortical activity.Network Plasticity as Bayesian InferenceWhere's the Noise? Key Features of Spontaneous Activity and Neural Variability Arise through Learning in a Deterministic Network.Memory replay in balanced recurrent networksUnsupervised learning in probabilistic neural networks with multi-state metal-oxide memristive synapses.Recurrent Spiking Networks Solve Planning Tasks.Itinerancy between attractor states in neural systems.A compound memristive synapse model for statistical learning through STDP in spiking neural networksLearning Probabilistic Inference through Spike-Timing-Dependent Plasticity.Probabilistic inference in discrete spaces can be implemented into networks of LIF neurons.Exploring the limits of learning: Segregation of information integration and response selection is required for learning a serial reversal task.Conduction Delay Learning Model for Unsupervised and Supervised Classification of Spatio-Temporal Spike Patterns.Winner-take-all in a phase oscillator system with adaptation.Memory States and Transitions between Them in Attractor Neural Networks.Bridging structure and function: A model of sequence learning and prediction in primary visual cortex.Neural Correlate of Transition Violation and Deviance Detection in the Songbird Auditory ForebrainProbabilistic Inference in Neural NetworksGeneral differential Hebbian learning: Capturing temporal relations between events in neural networks and the brain
P2860
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P2860
STDP installs in Winner-Take-All circuits an online approximation to hidden Markov model learning
description
2014 nî lūn-bûn
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2014 թուականի Մարտին հրատարակուած գիտական յօդուած
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2014 թվականի մարտին հրատարակված գիտական հոդված
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2014年の論文
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2014年論文
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2014年論文
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2014年論文
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2014年論文
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2014年論文
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2014年论文
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name
STDP installs in Winner-Take-A ...... o hidden Markov model learning
@ast
STDP installs in Winner-Take-A ...... o hidden Markov model learning
@en
type
label
STDP installs in Winner-Take-A ...... o hidden Markov model learning
@ast
STDP installs in Winner-Take-A ...... o hidden Markov model learning
@en
prefLabel
STDP installs in Winner-Take-A ...... o hidden Markov model learning
@ast
STDP installs in Winner-Take-A ...... o hidden Markov model learning
@en
P2860
P1476
STDP installs in Winner-Take-A ...... o hidden Markov model learning
@en
P2093
Bernhard Nessler
David Kappel
P2860
P304
P356
10.1371/JOURNAL.PCBI.1003511
P577
2014-03-27T00:00:00Z