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Spiking Neural Networks - Part II: Detecting Spatio-Temporal Patterns
Nicolas Skatchkovsky
, Hyeryung Jang
, Osvaldo Simeone
Electrical and Computer Engineering
Research output
:
Contribution to journal
›
Article
›
peer-review
24
Scopus citations
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Dive into the research topics of 'Spiking Neural Networks - Part II: Detecting Spatio-Temporal Patterns'. Together they form a unique fingerprint.
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Engineering
Learning Rule
100%
Network Model
50%
Backpropagation
50%
Recurrent Neural Network
50%
Data Type
50%
Review Paper
50%
Neuroprosthetics
50%
Spiking Neuron
50%
Activation Function
50%
Nondifferentiability
50%
Spatiotemporal Processing
50%
Model Review
50%
Keyphrases
Spiking Neural Networks
100%
Spatiotemporal Pattern
100%
Spiking Neurons
16%
Neural Prosthesis
16%
Modeling Algorithm
16%
Training Algorithm
16%
Recurrent Neural Network
16%
Rule-based
16%
Probabilistic Model
16%
First Review
16%
Tweets
16%
Stamping
16%
Learning Rule
16%
Spatiotemporal Processing
16%
Activation Function
16%
Gradient Estimate
16%
Non-differentiability
16%
Biological Brain
16%
Neuromorphic Sensors
16%
Differentiable Function
16%
Stochastic Estimates
16%
Neuromorphic Data
16%
Local Learning Rules
16%
Backpropagation through Time
16%
Review Model
16%
Surrogate Gradient
16%
Mathematics
Neural Network
100%
Learning Rule
28%
Stochastics
14%
Differentiability
14%
Approximates
14%
Network Model
14%
Spiking Neuron
14%
Data Type
14%
Differentiable Function
14%
Computer Science
Neural Network
100%
Neural Network Model
20%
training algorithm
20%
Backpropagation
20%
Data Type
20%
Recurrent Neural Network
20%
Activation Function
20%
Material Science
Probabilistic Model
100%
Neural Prosthesis
100%