Blessing of dimensionality in spiking neural networks: the by-chance functional learning
Spiking neural networks (SNNs) have significant potential for a power-efficient neuromorphic AI. However, their training is challenging since most of the learning principles known from artificial neural networks are hardly applicable. Recently, the concept of “blessing of dimensionality” has success...
Saved in:
| Main Authors: | Valeri A. Makarov, Sergey A. Lobov |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-06-01
|
| Series: | Frontiers in Applied Mathematics and Statistics |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fams.2025.1553779/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Continual learning with hebbian plasticity in sparse and predictive coding networks: a survey and perspective
by: Ali Safa
Published: (2024-01-01) -
Advancing EEG based stress detection using spiking neural networks and convolutional spiking neural networks
by: Aaditya Joshi, et al.
Published: (2025-07-01) -
An Efficient Neural Cell Architecture for Spiking Neural Networks
by: Kasem Khalil, et al.
Published: (2025-01-01) -
NeuBridge: bridging quantized activations and spiking neurons for ANN-SNN conversion
by: Yuchen Yang, et al.
Published: (2025-01-01) -
Short-term plasticity influences episodic memory recall: an interplay of synaptic traces in a spiking neural network model
by: N. Chrysanthidis, et al.
Published: (2025-08-01)