7.7k citations · 7.8k across the 9 of their papers we have counts for
10 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…
A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware
Eric Müller, Elias Arnold, Oliver Breitwieser +20
Neuromorphic systems open up opportunities to enlarge the explorative space for computational research. However, it is often challenging to unite efficiency and usability. This wor…
Variational learning of quantum ground states on spiking neuromorphic hardware
Robert Klassert, Andreas Baumbach, Mihai A. Petrovici +1
Recent research has demonstrated the usefulness of neural networks as variational ansatz functions for quantum many-body states. However, high-dimensional sampling spaces and trans…
Spiking neuromorphic chip learns entangled quantum states
Stefanie Czischek, Andreas Baumbach, Sebastian Billaudelle +8
The approximation of quantum states with artificial neural networks has gained a lot of attention during the last years. Meanwhile, analog neuromorphic chips, inspired by structura…
Cortical oscillations implement a backbone for sampling-based computation in spiking neural networks
Agnes Korcsak-Gorzo, Michael G. Müller, Andreas Baumbach +7
Being permanently confronted with an uncertain world, brains have faced evolutionary pressure to represent this uncertainty in order to respond appropriately. Often, this requires…
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…
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…
The Astropy Project: Building an inclusive, open-science project and status of the v2.0 core package
The Astropy Collaboration, A. M. Price-Whelan, B. M. Sipőcz +134
The Astropy project supports and fosters the development of open-source and openly-developed Python packages that provide commonly-needed functionality to the astronomical communit…