juyongjiang / TrendGCN

[CIKM 2023] This is the official source code of "TrendGCN: Enhancing the Robustness via Adversarial Learning and Joint Spatial-Temporal Embeddings in Traffic Forecasting" based on Pytorch.

Date Created 2022-06-30 (2 years ago)

Commits 28 (last one about a year ago)

Stargazers 48 (0 this week)

Watchers 2 (0 this week)

Forks 2

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RepositoryStats indexes 632,869 repositories, of these juyongjiang/TrendGCN is ranked #503,530 (20th percentile) for total stargazers, and #481,903 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #98,542/129,221.

juyongjiang/TrendGCN is also tagged with popular topics, for these it's ranked: deep-learning (#7,445/8814), generative-adversarial-network (#326/381), graph-convolutional-networks (#101/112), time-series-forecasting (#94/111)

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juyongjiang/TrendGCN has Github issues enabled, there are 2 open issues and 2 closed issues.

Homepage URL: https://arxiv.org/abs/2208.03063

All Topics

deep-learning dynamic-graph adaptive-graph traffic-forecasting time-series-forecasting graph-convolutional-networks generative-adversarial-network

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28 commits on the default branch (master) since jan '22

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updated: 2025-03-15 @ 04:34pm, id: 509061950 / R_kgDOHlerPg