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News/Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution
arxiv
PublishedApril 30, 2026 at 4:00 AM
▲bullish

Efficient Traffic Forecasting on Large-Scale Road Network by Regularized Adaptive Graph Convolution

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2506.07179v2 Announce Type: replace-cross Abstract: Traffic prediction is a critical task in spatial-temporal forecasting with broad applications in travel planning and urban management. To model the complex spatial-temporal dependencies in traffic data, Spatial-Temporal Graph Convolutional Ne

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Discussion
Mentioned models
02
  • 01
    Spatial-Temporal Graph Convolutional Networks (STGCNs)
  • 02
    Regularized Adaptive Graph Convolution (RAGC)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine-learning#traffic-prediction#graph-convolution#scalability

No replies yet. Be first.

Mentioned models
02
  • 01
    Spatial-Temporal Graph Convolutional Networks (STGCNs)
  • 02
    Regularized Adaptive Graph Convolution (RAGC)
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#machine-learning#traffic-prediction#graph-convolution#scalability

Related coverage

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