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Training Large Spiking Neural Networks from Scratch

Training large Spiking Neural Networks (SNNs) from random initialization is challenging due to vanishing gradients. Existing methods often rely on ANN-to-SNN conversion or distillation. The author faced budget constraints while attempting to scale an SNN to 1.088B parameters from scratch.

Computing & Technology, Computer Science, Artificial Intelligence