4 citations · 4 across the 2 of their papers we have counts for
3 papers
Gradient-based methods for spiking physical systems
Julian Göltz, Sebastian Billaudelle, Laura Kriener +5
Recent efforts have fostered significant progress towards deep learning in spiking networks, both theoretical and in silico. Here, we discuss several different approaches, includin…
Event-based Backpropagation for Analog Neuromorphic Hardware
Christian Pehle, Luca Blessing, Elias Arnold +2
Neuromorphic computing aims to incorporate lessons from studying biological nervous systems in the design of computer architectures. While existing approaches have successfully imp…
hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2
Philipp Spilger, Elias Arnold, Luca Blessing +4
Neuromorphic systems require user-friendly software to support the design and optimization of experiments. In this work, we address this need by presenting our development of a mac…