71 citations · 148 across the 14 of their papers we have counts for
10 papers
jaxsnn: Event-driven Gradient Estimation for Analog Neuromorphic Hardware
Eric Müller, Moritz Althaus, Elias Arnold +3
Traditional neuromorphic hardware architectures rely on event-driven computation, where the asynchronous transmission of events, such as spikes, triggers local computations within…
Emulating insect brains for neuromorphic navigation
Korbinian Schreiber, Timo Wunderlich, Philipp Spilger +8
Bees display the remarkable ability to return home in a straight line after meandering excursions to their environment. Neurobiological imaging studies have revealed that this capa…
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…
From Clean Room to Machine Room: Commissioning of the First-Generation BrainScaleS Wafer-Scale Neuromorphic System
Hartmut Schmidt, José Montes, Andreas Grübl +9
The first-generation of BrainScaleS, also referred to as BrainScaleS-1, is a neuromorphic system for emulating large-scale networks of spiking neurons. Following a "physical modeli…
Spiking Neural Network Nonlinear Demapping on Neuromorphic Hardware for IM/DD Optical Communication
Elias Arnold, Georg Böcherer, Florian Strasser +7
Neuromorphic computing implementing spiking neural networks (SNN) is a promising technology for reducing the footprint of optical transceivers, as required by the fast-paced growth…
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…