1 citations · 2 across the 3 of their papers we have counts for
3 papers
Cross-Frequency Coupling Increases Memory Capacity in Oscillatory Neural Networks
Connor Bybee, Alexander Belsten, Friedrich T. Sommer
An open problem in neuroscience is to explain the functional role of oscillations in neural networks, contributing, for example, to perception, attention, and memory. Cross-frequen…
Deep Learning in Spiking Phasor Neural Networks
Connor Bybee, E. Paxon Frady, Friedrich T. Sommer
Spiking Neural Networks (SNNs) have attracted the attention of the deep learning community for use in low-latency, low-power neuromorphic hardware, as well as models for understand…
NxTF: An API and Compiler for Deep Spiking Neural Networks on Intel Loihi
Bodo Rueckauer, Connor Bybee, Ralf Goettsche +3
Spiking Neural Networks (SNNs) are a promising paradigm for efficient event-driven processing of spatio-temporally sparse data streams. SNNs have inspired the design and can take a…