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Numerical computations were performed using NumPy 1.26.4 (Harris et al., 2020) and SciPy 1.15.3 (Virtanen et al., 2020)

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1 Pith paper citing it

fields

cs.LG 1

years

2026 1

verdicts

UNVERDICTED 1

representative citing papers

ChronoSpike: An Adaptive Spiking Graph Neural Network for Dynamic Graphs

cs.LG · 2026-02-01 · unverdicted · novelty 7.0

ChronoSpike is a spiking GNN that integrates adaptive LIF neurons with spatial attention and temporal transformers to outperform baselines on dynamic graph benchmarks by 2% F1 while training 3-10x faster with fixed parameters and stability guarantees.

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  • ChronoSpike: An Adaptive Spiking Graph Neural Network for Dynamic Graphs cs.LG · 2026-02-01 · unverdicted · none · ref 16

    ChronoSpike is a spiking GNN that integrates adaptive LIF neurons with spatial attention and temporal transformers to outperform baselines on dynamic graph benchmarks by 2% F1 while training 3-10x faster with fixed parameters and stability guarantees.