activity
20192023
most citedThe Heidelberg spiking datasets for the systematic evaluation of spiking neural networks

296 citations · 463 across the 11 of their papers we have counts for

collaborators

13 papers

cs.NE2023

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…

q-bio.NC2023

Signatures of hierarchical temporal processing in the mouse visual system

Lucas Rudelt, Daniel González Marx, F. Paul Spitzner +3

A core challenge for the brain is to process information across various timescales. This could be achieved by a hierarchical organization of temporal processing through intrinsic m…

q-bio.NC2022★ 1 cited

Autocorrelations from emergent bistability in homeostatic spiking neural networks on neuromorphic hardware

Benjamin Cramer, Markus Kreft, Sebastian Billaudelle +9

A unique feature of neuromorphic computing is that memory is an implicit part of processing through traces of past information in the system's collective dynamics. The extent of me…

cs.NE2022

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…

cs.NE2022★ 2 cited

The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity

Christian Pehle, Sebastian Billaudelle, Benjamin Cramer +7

Since the beginning of information processing by electronic components, the nervous system has served as a metaphor for the organization of computational primitives. Brain-inspired…

cs.ET2020★ 12 cited

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…