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ChronoSpike: An Adaptive Spiking Graph Neural Network for Dynamic Graphs
Dynamic graph representation learning requires capturing both structural relations and temporal evolution, yet existing approaches face a core trade-off: attention-based methods offer expressiveness at O(T^2) complexity, while recurrent architectures suffer from gradient pathologies and dense state
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