XOResNet: Exclusive-OR Meta-Residuals Facilitate Deep Spiking Neural Networks Learning
Researchers have developed XOResNet, a novel architecture for deep spiking neural networks (SNNs) that improves learning and representation capabilities. The design incorporates an OR-ADD shortcut connection to better merge outputs from different branches and utilizes XOR meta-residuals to reduce redundant learning in the backbone. Experiments on multiple datasets demonstrate that XOResNet surpasses current state-of-the-art deep SNNs, offering new insights for high-performance neuromorphic systems. AI
IMPACT Introduces a new architecture that improves performance on several benchmark datasets for spiking neural networks.