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

<https://repo.masters-masters.com/en/repos/lin-shuyu/VAE-LSTM-for-anomaly-detection>

[Home](https://repo.masters-masters.com/en) › [lin-shuyu](https://repo.masters-masters.com/en/owners/lin-shuyu) › [VAE-LSTM-for-anomaly-detection](https://repo.masters-masters.com/en/repos/lin-shuyu/VAE-LSTM-for-anomaly-detection)

lin-shuyu/VAE-LSTM-for-anomaly-detection has 577 stars on GitHub. Its RepoMasters card: Alpha tier. We propose a VAE-LSTM model as an unsupervised learning…

| Field | Value |
| --- | --- |
| Owner | [lin-shuyu](https://repo.masters-masters.com/en/owners/lin-shuyu) |
| Stars | 577 |
| Forks | 95 |
| Language | [Jupyter Notebook](https://repo.masters-masters.com/en/languages/jupyter-notebook) |
| License | None |
| Created | 2020 |
| Topics | anomaly-detection, unsupervised-learning, variational-autoencoder, time-series, tensorflow |
| Tier | [Alpha (250 to 699 ★)](https://repo.masters-masters.com/en/ranks/b_movie) |
| View on GitHub | [lin-shuyu/VAE-LSTM-for-anomaly-detection](https://github.com/lin-shuyu/VAE-LSTM-for-anomaly-detection) |

## Repository

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

The tier for repos with 250 to 699 ★. Published odds per card pulled: 20%. Rarity: Uncommon.

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Data: GitHub · Illustration drawn by RepoMasters from the repo’s ID and its language color.