2026
Narrowing the ANN–SNN Gap for 1D Signal Classification with Multi-Scale Temporal Encoding and Sparsity-Regularized Transform Encoding
ICML 2026poster
Spiking neural networks (SNNs) promise energy-efficient inference, yet on static vision benchmarks they often trail matched ANNs under short simulation horizons. Under a matched-backbone and matched-budget protocol without extra tricks, we find that this ANN-SNN accuracy gap is consistently smaller …