Author

Changze Lv

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#artificial intelligence Preprint Sep 2026

SpikeLite: Lightweight Spiking Neural Networks for Time-Series Forecasting

Spiking neural networks (SNNs) offer an energy-efficient paradigm for time-series forecasting through spike-driven computation. However, recent SNN forecasters often pursue higher accuracy through increasingly complex attention mechanisms, or specialized neuronal dynamics, weakening the lightweight motivation of SNNs....

Bang Hu, Chang-Ze Lv, Ming-Jie Li et al. · 0 citations

Jul 2026

Enhancing spiking transformers with temporal feedback coding and global-local dynamic neurons.

This work introduces a Temporal Feedback Coding (TFC) scheme that leverages feedback at the encoding stage to diversify spike patterns and designs a Global-Local Dynamic LIF (GLD-LIF) neuron that enhances cross-step dependency modeling by integrating local aggregation and global initialization.

Zeqi Zheng, Zizheng Zhu, Yingchao Yu et al. · Neural Networks · 0 citations