138 citations · 268 across the 6 of their papers we have counts for
7 papers
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…
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…
Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network
Timo C. Wunderlich, Akos F. Kungl, Eric Müller +2
Future developments in artificial intelligence will profit from the existence of novel, non-traditional substrates for brain-inspired computing. Neuromorphic computers aim to provi…
Demonstrating Advantages of Neuromorphic Computation: A Pilot Study
Timo Wunderlich, Akos F. Kungl, Eric Müller +14
Neuromorphic devices represent an attempt to mimic aspects of the brain's architecture and dynamics with the aim of replicating its hallmark functional capabilities in terms of com…
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…
Accelerated physical emulation of Bayesian inference in spiking neural networks
Akos F. Kungl, Sebastian Schmitt, Johann Klähn +21
The massively parallel nature of biological information processing plays an important role for its superiority to human-engineered computing devices. In particular, it may hold the…