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08/29/2023
Gradient-based methods for spiking physical systems
Recent efforts have fostered significant progress towards deep learning ...
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03/28/2023
Simulation-based Inference for Model Parameterization on Analog Neuromorphic Hardware
The BrainScaleS-2 (BSS-2) system implements physical models of neurons a...
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03/22/2023
From Clean Room to Machine Room: Commissioning of the First-Generation BrainScaleS Wafer-Scale Neuromorphic System
The first-generation of BrainScaleS, also referred to as BrainScaleS-1, ...
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02/13/2023
Event-based Backpropagation for Analog Neuromorphic Hardware
Neuromorphic computing aims to incorporate lessons from studying biologi...
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12/23/2022
hxtorch.snn: Machine-learning-inspired Spiking Neural Network Modeling on BrainScaleS-2
Neuromorphic systems require user-friendly software to support the desig...
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09/19/2022
An accurate and flexible analog emulation of AdEx neuron dynamics in silicon
Analog neuromorphic hardware promises fast brain emulation on the one ha...
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05/09/2022
Spiking Neural Network Equalization for IM/DD Optical Communication
A spiking neural network (SNN) equalizer model suitable for electronic n...
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03/21/2022
A Scalable Approach to Modeling on Accelerated Neuromorphic Hardware
Neuromorphic systems open up opportunities to enlarge the explorative sp...
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02/24/2022
Demonstrating BrainScaleS-2 Inter-Chip Pulse-Communication using EXTOLL
The BrainScaleS-2 (BSS-2) Neuromorphic Computing System currently consis...
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01/26/2022
The BrainScaleS-2 accelerated neuromorphic system with hybrid plasticity
Since the beginning of information processing by electronic components, ...
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11/30/2021
BrainScaleS Large Scale Spike Communication using Extoll
The BrainScaleS Neuromorphic Computing System is currently connected to ...
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03/29/2021
Demonstrating Analog Inference on the BrainScaleS-2 Mobile System
We present the BrainScaleS-2 mobile system as a compact analog inference...
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08/03/2020
Spiking neuromorphic chip learns entangled quantum states
Neuromorphic systems are designed to emulate certain structural and dyna...
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06/23/2020
Inference with Artificial Neural Networks on Analog Neuromorphic Hardware
The neuromorphic BrainScaleS-2 ASIC comprises mixed-signal neurons and s...
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06/23/2020
Inference with Artificial Neural Networks on the Analog BrainScaleS-2 Hardware
The neuromorphic BrainScaleS-2 ASIC comprises mixed-signal neurons and s...
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06/23/2020
hxtorch: PyTorch for BrainScaleS-2 – Perceptrons on Analog Neuromorphic Hardware
We present software facilitating the usage of the BrainScaleS-2 analog n...
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06/23/2020
hxtorch: PyTorch for ANNs on BrainScaleS-2
We present software facilitating the usage of the BrainScaleS-2 analog n...
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06/12/2020
Training spiking multi-layer networks with surrogate gradients on an analog neuromorphic substrate
Spiking neural networks are nature's solution for parallel information p...
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03/30/2020
Extending BrainScaleS OS for BrainScaleS-2
BrainScaleS-2 is a mixed-signal accelerated neuromorphic system targeted...
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03/30/2020
The Operating System of the Neuromorphic BrainScaleS-1 System
BrainScaleS-1 is a wafer-scale mixed-signal accelerated neuromorphic sys...
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03/26/2020
Accelerated Analog Neuromorphic Computing
This paper presents the concepts behind the BrainScales (BSS) accelerate...
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03/25/2020
Verification and Design Methods for the BrainScaleS Neuromorphic Hardware System
This paper presents verification and implementation methods that have be...
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12/30/2019
Versatile emulation of spiking neural networks on an accelerated neuromorphic substrate
We present first experimental results on the novel BrainScaleS-2 neuromo...
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12/27/2019
Structural plasticity on an accelerated analog neuromorphic hardware system
In computational neuroscience, as well as in machine learning, neuromorp...
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12/24/2019
Fast and deep neuromorphic learning with time-to-first-spike coding
For a biological agent operating under environmental pressure, energy co...
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10/16/2019
The Heidelberg spiking datasets for the systematic evaluation of spiking neural networks
Spiking neural networks are the basis of versatile and power-efficient i...
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09/24/2019
Brain-Inspired Hardware for Artificial Intelligence: Accelerated Learning in a Physical-Model Spiking Neural Network
Future developments in artificial intelligence will profit from the exis...
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09/17/2019
Control of criticality and computation in spiking neuromorphic networks with plasticity
The critical state is assumed to be optimal for any computation in recur...
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11/08/2018
Demonstrating Advantages of Neuromorphic Computation: A Pilot Study
Neuromorphic devices represent an attempt to mimic aspects of the brain'...
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09/21/2018
Stochasticity from function - why the Bayesian brain may need no noise
An increasing body of evidence suggests that the trial-to-trial variabil...
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07/06/2018
Generative models on accelerated neuromorphic hardware
The traditional von Neumann computer architecture faces serious obstacle...
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05/23/2018
Large-Scale Neuromorphic Spiking Array Processors: A quest to mimic the brain
Neuromorphic engineering (NE) encompasses a diverse range of approaches ...
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01/15/2018
Full Wafer Redistribution and Wafer Embedding as Key Technologies for a Multi-Scale Neuromorphic Hardware Cluster
Together with the Kirchhoff-Institute for Physics(KIP) the Fraunhofer IZ...
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09/24/2017
Spiking neurons with short-term synaptic plasticity form superior generative networks
Spiking networks that perform probabilistic inference have been proposed...
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03/21/2017
An Accelerated Analog Neuromorphic Hardware System Emulating NMDA- and Calcium-Based Non-Linear Dendrites
This paper presents an extension of the BrainScaleS accelerated analog n...
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03/17/2017
Pattern representation and recognition with accelerated analog neuromorphic systems
Despite being originally inspired by the central nervous system, artific...
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03/12/2017
Robustness from structure: Inference with hierarchical spiking networks on analog neuromorphic hardware
How spiking networks are able to perform probabilistic inference is an i...
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03/06/2017
Neuromorphic Hardware In The Loop: Training a Deep Spiking Network on the BrainScaleS Wafer-Scale System
Emulating spiking neural networks on analog neuromorphic hardware offers...
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10/23/2016
Stochastic inference with spiking neurons in the high-conductance state
The highly variable dynamics of neocortical circuits observed in vivo ha...
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04/18/2016
Demonstrating Hybrid Learning in a Flexible Neuromorphic Hardware System
We present results from a new approach to learning and plasticity in neu...
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01/05/2016
The high-conductance state enables neural sampling in networks of LIF neurons
The apparent stochasticity of in-vivo neural circuits has long been hypo...
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04/29/2014
Characterization and Compensation of Network-Level Anomalies in Mixed-Signal Neuromorphic Modeling Platforms
Advancing the size and complexity of neural network models leads to an e...
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11/13/2013