aptx1231/Traffic-Prediction-Open-Code-Summary

Summary of open source code for deep learning models in the field of traffic prediction

41
/ 100
Emerging

Curated collection of 30+ spatio-temporal deep learning architectures for traffic prediction across six task categories (flow, speed, travel time, accidents, etc.), with implementations in TensorFlow, PyTorch, and MXNet. Models progress from CNN-LSTM baselines to graph neural networks (GCN, GNN-ODE) and attention mechanisms, capturing both spatial road network topology and temporal dependencies. Includes peer-reviewed papers from top venues (AAAI, KDD, NIPS) with direct links to official and community implementations across frameworks.

279 stars. No commits in the last 6 months.

Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 9 / 25
Community 22 / 25

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Stars

279

Forks

60

Language

License

MIT

Last pushed

Nov 17, 2022

Commits (30d)

0

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