# jwwthu/GNN4Traffic

This is the repository for the collection of Graph Neural Network for Traffic Forecasting.

Repository: https://github.com/jwwthu/GNN4Traffic
Canonical: https://ross.abutalabs.com/products/gnn4traffic
License Family: other
Last push: 2024-08-07T11:55:53+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2323, "days_push": 756, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1212, forks 190 (observed 2026-08-28T04:04:00.353585+00:00)

## What it is
A curated collection of research papers on Graph Neural Networks for traffic forecasting, accompanying published surveys. It includes paper statistics and links to related repositories on deep learning for traffic and spatio-temporal data mining.

## Use cases
- find papers on graph neural networks for traffic prediction
- survey the state of the art in GNN-based traffic forecasting
- research spatio-temporal deep learning for transportation
- find datasets and baselines for traffic flow prediction
- track recent publications on traffic estimation with GNNs

## When to choose
- you are doing a literature review on GNNs for traffic forecasting
- you need a curated paper list with publication statistics
- you want pointers to related deep learning traffic resources

## When to avoid
- you need runnable code or a software library
- you need production traffic prediction systems rather than research papers

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, data-science
- domain: machine-learning, artificial-intelligence, awesome-lists, tutorials
- platform: cross-platform
- tags: awesome-list, graph-neural-networks, traffic-forecasting, survey, paper-collection, spatio-temporal, transportation-research

## Member repositories
- jwwthu/GNN4Traffic (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:00.353585+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:18:00.302318+00:00, confidence not recorded.
  - readme: https://github.com/jwwthu/GNN4Traffic (fetched 2026-08-28T04:04:00.353585+00:00, sha 216d7499b869)
- Data as of 2026-08-30T08:39:29.467469+00:00.