5 citations · 5 across the 1 of their papers we have counts for
3 papers · 1 filter
Spike-based alignment learning solves the weight transport problem
Timo Gierlich, Andreas Baumbach, Akos F. Kungl +2
In both machine learning and in computational neuroscience, plasticity in functional neural networks is frequently expressed as gradient descent on a cost. Often, this imposes symm…
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…
Stochasticity from function -- why the Bayesian brain may need no noise
Dominik Dold, Ilja Bytschok, Akos F. Kungl +6
An increasing body of evidence suggests that the trial-to-trial variability of spiking activity in the brain is not mere noise, but rather the reflection of a sampling-based encodi…