Although spiking neural networks (SNNs) show promise in energy-efficient computing through event-driven computation and stateful temporal processing, their recurrent membrane dynamics render their training inherently sequential and inefficient for long sequences. Existing methods achieve full-sequence parallelism in SN...
DS-VLA is introduced, a dendritic-inspired action architecture that incorporates dendritic spiking dynamics into VLA control to enable modularized feature processing and temporal information integration and demonstrate that integrating brain-inspired computational mechanisms offers a promising architectural prior for r...
Inspired by underlying neural processing mechanisms, a novel view incremental learning framework named Hebbian View Orthogonal Projection is proposed, which constructs a knowledge transfer space, where gradient updates are projected onto the orthogonal complement of historical representations, thereby mitigating interf...
Yu-Hong Chen, Zi-Han Fang, Hui-Feng Yin et al.· Proceedings of the Thirty-Fi...· 0 citations
The proposed parallel multi-compartment spiking neuron (PMSN) presents a promising solution to harness the computational advantages of detailed biological neurons, enabling high-performance and efficient temporal processing on neuromorphic computing systems.
Xinyi Chen, Jibin Wu, Chenxiang Ma et al.· IEEE Transactions on Neural...· 16 citations· ⚡4
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