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06/04/2023
Random Feedback Alignment Algorithms to train Neural Networks: Why do they Align?
Feedback alignment algorithms are an alternative to backpropagation to t...
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12/15/2022
Exact Error Backpropagation Through Spikes for Precise Training of Spiking Neural Networks
Event-based simulations of Spiking Neural Networks (SNNs) are fast and a...
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12/14/2022
Directional Direct Feedback Alignment: Estimating Backpropagation Paths for Efficient Learning on Neural Processors
The error Backpropagation algorithm (BP) is a key method for training de...
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05/09/2022
Programming molecular systems to emulate a learning spiking neuron
Hebbian theory seeks to explain how the neurons in the brain adapt to st...
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06/28/2021
Integrate-and-Fire Neurons for Low-Powered Pattern Recognition
Embedded systems acquire information about the real world from sensors a...
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03/10/2021
Linear Constraints Learning for Spiking Neurons
Encoding information with precise spike timings using spike-coded neuron...
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12/14/2020
Constraints on Hebbian and STDP learned weights of a spiking neuron
We analyse mathematically the constraints on weights resulting from Hebb...
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09/28/2020
A thermodynamically consistent chemical spiking neuron capable of autonomous Hebbian learning
We propose a fully autonomous, thermodynamically consistent set of chemi...
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03/05/2020