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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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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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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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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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09/17/2020
EventProp: Backpropagation for Exact Gradients in Spiking Neural Networks
We derive the backpropagation algorithm for spiking neural networks comp...
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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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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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03/15/2019
Neuromorphic Hardware learns to learn
Hyperparameters and learning algorithms for neuromorphic hardware are us...
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11/08/2018