Search Results for author:
Found 2 papers, 1 papers with code
Understanding the Functional Roles of Modelling Components in Spiking Neural Networks
By designing and evaluating several variants of the classic model, we systematically investigate the functional roles of key modelling components, leakage, reset, and recurrence, in leaky integrate-and-fire (LIF) based SNNs.
Going Deeper With Directly-Trained Larger Spiking Neural Networks
To this end, we propose a threshold-dependent batch normalization (tdBN) method based on the emerging spatio-temporal backpropagation, termed "STBP-tdBN", enabling direct training of a very deep SNN and the efficient implementation of its inference on neuromorphic hardware.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
