189 citations · 1.4k across the 34 of their papers we have counts for
35 papers
Closed-loop experiments on the BrainScaleS-2 architecture
K. Schreiber, T. C. Wunderlich, C. Pehle +3
The evolution of biological brains has always been contingent on their embodiment within their respective environments, in which survival required appropriate navigation and manipu…
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
Sebastian Billaudelle, Yannik Stradmann, Korbinian Schreiber +22
We present first experimental results on the novel BrainScaleS-2 neuromorphic architecture based on an analog neuro-synaptic core and augmented by embedded microprocessors for comp…
Structural plasticity on an accelerated analog neuromorphic hardware system
Sebastian Billaudelle, Benjamin Cramer, Mihai A. Petrovici +4
In computational neuroscience, as well as in machine learning, neuromorphic devices promise an accelerated and scalable alternative to neural network simulations. Their neural conn…
Fast and energy-efficient neuromorphic deep learning with first-spike times
Julian Göltz, Laura Kriener, Andreas Baumbach +9
For a biological agent operating under environmental pressure, energy consumption and reaction times are of critical importance. Similarly, engineered systems are optimized for sho…
Control of criticality and computation in spiking neuromorphic networks with plasticity
Benjamin Cramer, David Stöckel, Markus Kreft +4
The critical state is assumed to be optimal for any computation in recurrent neural networks, because criticality maximizes a number of abstract computational properties. We challe…
Neuromorphic Hardware learns to learn
Thomas Bohnstingl, Franz Scherr, Christian Pehle +2
Hyperparameters and learning algorithms for neuromorphic hardware are usually chosen by hand. In contrast, the hyperparameters and learning algorithms of networks of neurons in the…