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Found 5 papers, 1 papers with code
Astrocyte control bursting mode of spiking neuron network with memristor-implemented plasticity
The network is composed of excitatory and inhibitory neurons with synaptic connections supplied by a memristor-based model of plasticity.
Dynamic image recognition in a spiking neuron network supplied by astrocytes
Mathematical model of spiking neuron network (SNN) supplied by astrocytes is investigated.
Failure of neuron network coherence induced by SARS-CoV-2-infected astrocytes
These synchronous fluctuations in the electrical activity of the brain are also referred to as brain rhythms.
Domain Adaptation Principal Component Analysis: base linear method for learning with out-of-distribution data
Domain adaptation is a popular paradigm in modern machine learning which aims at tackling the problem of divergence (or shift) between the labeled training and validation datasets (source domain) and a potentially large unlabeled dataset (target domain).
High-dimensional separability for one- and few-shot learning
New stochastic separation theorems for data with fine-grained structure are formulated and proved.
