SeAl-KD improves SNN accuracy by equalizing competing logits at erroneous timesteps and reweighting temporal alignment using confidence and inter-timestep similarity.
Improving stability and per- formance of spiking neural networks through enhancing temporal consistency.Pattern Recognition, 159:111094,
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Not All Timesteps Matter Equally: Selective Alignment Knowledge Distillation for Spiking Neural Networks
SeAl-KD improves SNN accuracy by equalizing competing logits at erroneous timesteps and reweighting temporal alignment using confidence and inter-timestep similarity.