Carlo Wenig
1 indexed paper
Recent (6 mo)
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126
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Neural Computing×1ML×1
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2026
Quadratic integrate-and-fire neurons exhibit less fragmented loss landscapes and outperform leaky integrate-and-fire neurons in spike-based gradient descent
The paper demonstrates that quadratic integrate-and-fire (QIF) neurons are superior to leaky integrate-and-fire (LIF) neurons for gradient descent training in spiking neural networks because their continuous spiking dynamics result in smoother loss landscapes.
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