Computer Science
图时空增强学习
Graph Spatial-Temporal Augmentation LearningA machine learning framework that enhances graph neural networks by augmenting spatial and temporal data to improve cross-city traffic prediction accuracy. / 一种机器学习框架，通过增强空间和时间数据来提高跨城市交通预测的准确性。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-11-12 17:06:50
Sub-knowledge points
Graph Spatial-Temporal AugmentationCross-City Traffic Prediction
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Main parameters and performance indicators
Cross-city traffic prediction: The application domainGraph Neural Networks: The underlying model architectureSpatial-Temporal Augmentation: The core data enhancement technique
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Related literature
ranked by community starsGraph Spatial-Temporal Augmentation Learning for Cross-City Traffic PredictionOpen source
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1 recordsRecord title: Graph Spatial-Temporal Augmentation Learning.
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