QB-LIF uses a trainable quantization scale for burst neurons in SNNs to raise accuracy at ultra-low latency on vision and event datasets while preserving neuromorphic hardware compatibility.
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XOResNet combines OA shortcuts and XOR meta-residuals into a residual block to build deeper SNNs that outperform prior gradient-descent SNNs on Fashion-MNIST, CIFAR-10, CIFAR-100, and miniImageNet.
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QB-LIF: Learnable-Scale Quantized Burst Neurons for Efficient SNNs
QB-LIF uses a trainable quantization scale for burst neurons in SNNs to raise accuracy at ultra-low latency on vision and event datasets while preserving neuromorphic hardware compatibility.
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XOResNet: Exclusive-OR Meta-Residuals Facilitate Deep Spiking Neural Networks Learning
XOResNet combines OA shortcuts and XOR meta-residuals into a residual block to build deeper SNNs that outperform prior gradient-descent SNNs on Fashion-MNIST, CIFAR-10, CIFAR-100, and miniImageNet.