lin-shuyu / VAE-LSTM-for-anomaly-detection

We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.

Date Created 2020-02-13 (4 years ago)

Commits 43 (last one 4 years ago)

Stargazers 465 (3 this week)

Watchers 10 (0 this week)

Forks 87

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RepositoryStats indexes 584,353 repositories, of these lin-shuyu/VAE-LSTM-for-anomaly-detection is ranked #95,659 (84th percentile) for total stargazers, and #206,270 for total watchers. Github reports the primary language for this repository as Jupyter Notebook, for repositories using this language it is ranked #2,031/17,098.

lin-shuyu/VAE-LSTM-for-anomaly-detection is also tagged with popular topics, for these it's ranked: tensorflow (#726/2241), time-series (#158/658), anomaly-detection (#61/328)

Other Information

lin-shuyu/VAE-LSTM-for-anomaly-detection has 3 open pull requests on Github, 1 pull request has been merged over the lifetime of the repository.

Github issues are enabled, there are 8 open issues and 3 closed issues.

All Topics

tensorflow time-series anomaly-detection unsupervised-learning variational-autoencoder

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updated: 2024-11-21 @ 06:27am, id: 240303624 / R_kgDODlK-CA