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To Spike or Not to Spike, that is the Question
Sanaz Mahmoodi Takaghaj
,
Jack Sampson
Computer Science and Engineering
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
Overview
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Dive into the research topics of 'To Spike or Not to Spike, that is the Question'. Together they form a unique fingerprint.
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Keyphrases
Spiking Neural Networks
100%
Hyperparameters
40%
Real-world Events
20%
Membrane Potential
20%
Training Methods
20%
Substantial Reduction
20%
Neural Network Learning
20%
Spatio-temporal Data
20%
Unique Properties
20%
Temporal Dynamics
20%
Learning Rate
20%
Biological Neuron
20%
Spike Timing
20%
Training Process
20%
Neuronal Membrane
20%
Effective Training
20%
Improved Convergence
20%
Heidelberg
20%
Spiking Activity
20%
Training Epochs
20%
Training Algorithm
20%
Training Intensity
20%
Vital Data
20%
Test Accuracy
20%
Effective Rate
20%
Neuromorphic Computing
20%
Event Processing
20%
Learning Rule
20%
Robust Training
20%
Neuromorphic Processor
20%
Training Methodology
20%
Neuromorphic Platform
20%
Training Parameters
20%
Computer Science
Neural Network
100%
Leaning Parameter
40%
Speed-up
20%
Unique Property
20%
Training Process
20%
Temporal Dynamic
20%
training algorithm
20%
Time-Event
20%
Neuroscience
Neural Network
100%
Behavior (Neuroscience)
20%
Membrane Potential
20%
Nerve Cell Membrane
20%
Earth and Planetary Sciences
Real Time
100%