Author

Zhaofei Yu

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#machine learning Preprint Oct 2026

Common-Mode Errors Limit Low-Timestep Deep Spiking Q-Networks

Spiking neural networks (SNNs) offer sparse and event-driven computation, making them attractive for energy-constrained reinforcement learning (RL) on edge devices. In value-based RL, deep spiking Q-networks (DSQNs) combine such efficiency with action-value estimation for decision making. However, existing DSQNs often...

Zi-Jie Xu, Bing-Rui Guo, Yi-Ding Sun et al. · 0 citations

Preprint Aug 2026

Reducing ANN-SNN Conversion Error via Residual Membrane Potential Alignment

This work analyzes flaws of conventional conversion pipelines from residual membrane potential statistics and proposes a novel conversion strategy combining dynamic initial potential tuning and feature enhancement, which generalizes to ReLU CNNs, ANN Transformers, and multi-threshold SNN variants.

Zirui Chen, Zihan Huang, Tong Bu et al. · 0 citations