#surrogate-gradients News & Analysis

Advancing Direct Training for Spiking Neural Networks with Circulate-Firing Neurons and Learnable Gradients

Researchers propose a novel direct training algorithm for Spiking Neural Networks that addresses performance gaps with traditional ANNs through circulate-firing neurons, learnable surrogate gradients, and balanced loss functions. The method demonstrates competitive results across datasets and extends effectively to Transformer architectures, potentially advancing energy-efficient neural network applications.