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Carlo Wenig

1 paper hereh-index 00 citations1 works total

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  • first author1

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  • cs.NE1

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collaborators

1 paper

cs.NE2026

Quadratic integrate-and-fire neurons exhibit less fragmented loss landscapes and outperform leaky integrate-and-fire neurons in spike-based gradient descent

Carlo Wenig, Raoul-Martin Memmesheimer, Christian Klos

The ability to train spiking neural networks is essential for modeling biological neural networks as well as for neuromorphic computing. However, for the extensively used leaky int…

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