Opportunities for neuromorphic computing algorithms and applications
Neuromorphic computing technologies will be important for the future of computing, but
much of the work in neuromorphic computing has focused on hardware development. Here …
much of the work in neuromorphic computing has focused on hardware development. Here …
Brain-inspired computing needs a master plan
New computing technologies inspired by the brain promise fundamentally different ways to
process information with extreme energy efficiency and the ability to handle the avalanche of …
process information with extreme energy efficiency and the ability to handle the avalanche of …
Spikingjelly: An open-source machine learning infrastructure platform for spike-based intelligence
Spiking neural networks (SNNs) aim to realize brain-inspired intelligence on neuromorphic
chips with high energy efficiency by introducing neural dynamics and spike properties. As …
chips with high energy efficiency by introducing neural dynamics and spike properties. As …
[HTML][HTML] A compute-in-memory chip based on resistive random-access memory
Realizing increasingly complex artificial intelligence (AI) functionalities directly on edge
devices calls for unprecedented energy efficiency of edge hardware. Compute-in-memory …
devices calls for unprecedented energy efficiency of edge hardware. Compute-in-memory …
Spike-driven transformer
Abstract Spiking Neural Networks (SNNs) provide an energy-efficient deep learning option
due to their unique spike-based event-driven (ie, spike-driven) paradigm. In this paper, we …
due to their unique spike-based event-driven (ie, spike-driven) paradigm. In this paper, we …
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 …
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 high-performance low-latency spiking neural networks by differentiation on spike representation
Abstract Spiking Neural Network (SNN) is a promising energy-efficient AI model when
implemented on neuromorphic hardware. However, it is a challenge to efficiently train SNNs …
implemented on neuromorphic hardware. However, it is a challenge to efficiently train SNNs …
Neuro-inspired computing chips
The rapid development of artificial intelligence (AI) demands the rapid development of
domain-specific hardware specifically designed for AI applications. Neuro-inspired …
domain-specific hardware specifically designed for AI applications. Neuro-inspired …
An interactive mouthguard based on mechanoluminescence-powered optical fibre sensors for bite-controlled device operation
Keyboards and touchscreens are widely used to control electronic devices, but these can be
difficult to operate for individuals with dexterity impairments or neurological conditions …
difficult to operate for individuals with dexterity impairments or neurological conditions …