Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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2 Pith papers cite this work, alongside 17 external citations. Polarity classification is still indexing.
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2026 2representative citing papers
In the Lightning Network, node degree mediates the effect of node lifetime on shared channel capacity, and country-level economic conditions significantly influence capacity distribution.
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Learning Dynamic Stability Landscapes in Synchronization Networks
Introduces graph-to-image prediction of per-node dynamic stability landscapes in oscillator networks from topology, releases two 10k-graph datasets, and shows GNN-CNN models achieve good accuracy with cross-size generalization.
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Shared Channel Capacity and Node Lifetime: An Empirical Study of the Lightning Network
In the Lightning Network, node degree mediates the effect of node lifetime on shared channel capacity, and country-level economic conditions significantly influence capacity distribution.