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MLGO: Multi-Layer graph neural ODEs for traffic forecasting
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AI
DOI：10.1016/j.neunet.2026.108540.png)
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Abstract
En 中文
• We propose a novel framework Multi-Layer Graph neural ordinary differential equations, which integrates multiple complementary graph structures. • Neural ODEs enable continuous spatial aggregation and alternated spatial-temporal updates, while avoiding overfitting. • Five real-world traffic datasets yielded promising predictive outcomes.