Training spiking neural networks using lessons from deep learning
The brain is the perfect place to look for inspiration to develop more efficient neural
networks. The inner workings of our synapses and neurons provide a glimpse at what the …
networks. The inner workings of our synapses and neurons provide a glimpse at what the …
Going deeper with directly-trained larger spiking neural networks
Spiking neural networks (SNNs) are promising in a bio-plausible coding for spatio-temporal
information and event-driven signal processing, which is very suited for energy-efficient …
information and event-driven signal processing, which is very suited for energy-efficient …
Training deep spiking neural networks
E Ledinauskas, J Ruseckas, A Juršėnas… - arXiv preprint arXiv …, 2020 - arxiv.org
Computation using brain-inspired spiking neural networks (SNNs) with neuromorphic
hardware may offer orders of magnitude higher energy efficiency compared to the current …
hardware may offer orders of magnitude higher energy efficiency compared to the current …
Deep neural networks with weighted spikes
Spiking neural networks are being regarded as one of the promising alternative techniques
to overcome the high energy costs of artificial neural networks. It is supported by many …
to overcome the high energy costs of artificial neural networks. It is supported by many …
Differentiable spike: Rethinking gradient-descent for training spiking neural networks
Abstract Spiking Neural Networks (SNNs) have emerged as a biology-inspired method
mimicking the spiking nature of brain neurons. This bio-mimicry derives SNNs' energy …
mimicking the spiking nature of brain neurons. This bio-mimicry derives SNNs' energy …
Training spiking neural networks with event-driven backpropagation
Abstract Spiking Neural networks (SNNs) represent and transmit information by
spatiotemporal spike patterns, which bring two major advantages: biological plausibility and …
spatiotemporal spike patterns, which bring two major advantages: biological plausibility and …
[HTML][HTML] Bindsnet: A machine learning-oriented spiking neural networks library in python
The development of spiking neural network simulation software is a critical component
enabling the modeling of neural systems and the development of biologically inspired …
enabling the modeling of neural systems and the development of biologically inspired …
Ternary spike: Learning ternary spikes for spiking neural networks
Y Guo, Y Chen, X Liu, W Peng, Y Zhang… - Proceedings of the …, 2024 - ojs.aaai.org
The Spiking Neural Network (SNN), as one of the biologically inspired neural network
infrastructures, has drawn increasing attention recently. It adopts binary spike activations to …
infrastructures, has drawn increasing attention recently. It adopts binary spike activations to …
Backpropagation-based learning techniques for deep spiking neural networks: A survey
M Dampfhoffer, T Mesquida… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
With the adoption of smart systems, artificial neural networks (ANNs) have become
ubiquitous. Conventional ANN implementations have high energy consumption, limiting …
ubiquitous. Conventional ANN implementations have high energy consumption, limiting …
Learning to be efficient: Algorithms for training low-latency, low-compute deep spiking neural networks
Recent advances have allowed Deep Spiking Neural Networks (SNNs) to perform at the
same accuracy levels as Artificial Neural Networks (ANNs), but have also highlighted a …
same accuracy levels as Artificial Neural Networks (ANNs), but have also highlighted a …