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Found 4 papers, 1 papers with code
A Practical Guide to Tuning Spiking Neuronal Dynamics
In this work, we examine fundamental elements of spiking neural networks (SNNs) as well as how to tune them.
Predictive Coding with Spiking Neural Networks: a Survey
In this article, we review a class of neuro-mimetic computational models that we place under the label of spiking predictive coding.
Time-Integrated Spike-Timing-Dependent-Plasticity
In this work, we propose time-integrated spike-timing-dependent plasticity (TI-STDP), a mathematical model of synaptic plasticity that allows spiking neural networks to continuously adapt to sensory input streams in an unsupervised fashion.
Predicted Embedding Power Regression for Large-Scale Out-of-Distribution Detection
Out-of-distribution (OOD) inputs can compromise the performance and safety of real world machine learning systems.
