2 papers
cs.CL2024
SpikingSSMs: Learning Long Sequences with Sparse and Parallel Spiking State Space Models
Shuaijie Shen, Chao Wang, Renzhuo Huang +5
Known as low energy consumption networks, spiking neural networks (SNNs) have gained a lot of attention within the past decades. While SNNs are increasing competitive with artifici…
cs.NE2024
SPikE-SSM: A Sparse, Precise, and Efficient Spiking State Space Model for Long Sequences Learning
Yan Zhong, Ruoyu Zhao, Chao Wang +4
Spiking neural networks (SNNs) provide an energy-efficient solution by utilizing the spike-based and sparse nature of biological systems. Since the advent of Transformers, SNNs hav…