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Changze Lv

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#artificial intelligence Preprint Sep 2026

SpikeLite: Lightweight Spiking Neural Networks for Time-Series Forecasting

Spiking forecasting framework SpikeLite is introduced, a spiking forecasting framework built around two modules: a Frequency-Selective Spiking Encoder for frequency-sensitive temporal encoding and a Sparse Spiking Channel Attention (SSCA) module for selective cross-channel interaction.

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. · 0 citations

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