activity
20182026
most citedThe Heidelberg spiking datasets for the systematic evaluation of spiking neural networks

296 citations · 697 across the 14 of their papers we have counts for

collaborators

15 papers

cs.NE2026

Real-time processing of analog signals on accelerated neuromorphic hardware

Yannik Stradmann, Johannes Schemmel, Mihai A. Petrovici +1

Sensory processing with neuromorphic systems is typically done by using either event-based sensors or translating input signals to spikes before presenting them to the neuromorphic…

cs.AR2025

Sustainable operation of research infrastructure for novel computing

Yannik Stradmann, Joscha Ilmberger, Eric Müller +1

Novel compute systems are an emerging research topic, aiming towards building next-generation compute platforms. For these systems to thrive, they need to be provided as research i…

q-bio.NC2024★ 3 cited

Lu.i -- A low-cost electronic neuron for education and outreach

Yannik Stradmann, Julian Göltz, Mihai A. Petrovici +2

With an increasing presence of science throughout all parts of society, there is a rising expectation for researchers to effectively communicate their work and, equally, for teache…

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…

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.AR2021★ 16 cited

Demonstrating Analog Inference on the BrainScaleS-2 Mobile System

Yannik Stradmann, Sebastian Billaudelle, Oliver Breitwieser +8

We present the BrainScaleS-2 mobile system as a compact analog inference engine based on the BrainScaleS-2 ASIC and demonstrate its capabilities at classifying a medical electrocar…

cs.NE2020★ 8 cited

Inference with Artificial Neural Networks on Analog Neuromorphic Hardware

Johannes Weis, Philipp Spilger, Sebastian Billaudelle +11

The neuromorphic BrainScaleS-2 ASIC comprises mixed-signal neurons and synapse circuits as well as two versatile digital microprocessors. Primarily designed to emulate spiking neur…

cs.NE2020★ 13 cited

hxtorch: PyTorch for BrainScaleS-2 -- Perceptrons on Analog Neuromorphic Hardware

Philipp Spilger, Eric Müller, Arne Emmel +10

We present software facilitating the usage of the BrainScaleS-2 analog neuromorphic hardware system as an inference accelerator for artificial neural networks. The accelerator hard…

cs.NE2020

Surrogate gradients for analog neuromorphic computing

Benjamin Cramer, Sebastian Billaudelle, Simeon Kanya +9

To rapidly process temporal information at a low metabolic cost, biological neurons integrate inputs as an analog sum but communicate with spikes, binary events in time. Analog neu…

q-bio.NC2019★ 43 cited

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…

cs.NE2019★ 296 cited

The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks

Benjamin Cramer, Yannik Stradmann, Johannes Schemmel +1

Spiking neural networks are the basis of versatile and power-efficient information processing in the brain. Although we currently lack a detailed understanding of how these network…

cs.NE2018★ 138 cited

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…

q-bio.NC2018★ 54 cited

A Mixed-Signal Structured AdEx Neuron for Accelerated Neuromorphic Cores

Syed Ahmed Aamir, Paul Müller, Gerd Kiene +5

Here we describe a multi-compartment neuron circuit based on the Adaptive-Exponential I&F (AdEx) model, developed for the second-generation BrainScaleS hardware. Based on an existi…

q-bio.NC2018★ 124 cited

An Accelerated LIF Neuronal Network Array for a Large Scale Mixed-Signal Neuromorphic Architecture

Syed Ahmed Aamir, Yannik Stradmann, Paul Müller +5

We present an array of leaky integrate-and-fire (LIF) neuron circuits designed for the second-generation BrainScaleS mixed-signal 65-nm CMOS neuromorphic hardware. The neuronal arr…