CATFormer: When Continual Learning Meets Spiking Transformers With Dynamic Thresholds
CATFormer: When Continual Learning Meets Spiking Transformers With Dynamic Thresholds explores CATFormer is a scalable framework that prevents catastrophic forgetting in spiking neural networks through dynamic thresholds.. Commercial viability score: 4/10 in Continual Learning.
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