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09/05/2023
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
Equilibrium propagation (EP) is a compelling alternative to the backprop...
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12/09/2022
Predictor networks and stop-grads provide implicit variance regularization in BYOL/SimSiam
Self-supervised learning (SSL) learns useful representations from unlabe...
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09/01/2022
Holomorphic Equilibrium Propagation Computes Exact Gradients Through Finite Size Oscillations
Equilibrium propagation (EP) is an alternative to backpropagation (BP) t...
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06/21/2022
Fluctuation-driven initialization for spiking neural network training
Spiking neural networks (SNNs) underlie low-power, fault-tolerant inform...
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05/30/2022
Braille Letter Reading: A Benchmark for Spatio-Temporal Pattern Recognition on Neuromorphic Hardware
Spatio-temporal pattern recognition is a fundamental ability of the brai...
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10/22/2020
Brain-Inspired Learning on Neuromorphic Substrates
Neuromorphic hardware strives to emulate brain-like neural networks and ...
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06/15/2020
Finding trainable sparse networks through Neural Tangent Transfer
Deep neural networks have dramatically transformed machine learning, but...
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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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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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01/28/2019
Surrogate Gradient Learning in Spiking Neural Networks
A growing number of neuromorphic spiking neural network processors that ...
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05/31/2017
SuperSpike: Supervised learning in multi-layer spiking neural networks
A vast majority of computation in the brain is performed by spiking neur...
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03/13/2017
