VAE-LSTM-for-anomaly-detection

lin-shuyu

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

tensorflow

View on GitHub

529 Stars

91 Forks

529 Watchers

Jupyter Notebook Language

Cost to Build

$10.2K

Market Value

$35.2K

How is this calculated?

Growth over time

1 data points · 2025-07-29 → 2025-07-29

Stars Forks Watchers

💬

How do you feel about this project?

Ask AI about VAE-LSTM-for-anomaly-detection

Question copied to clipboard

What is the lin-shuyu/VAE-LSTM-for-anomaly-detection GitHub project? Description: "We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.

Question is copied to clipboard — paste it after the AI opens.

How to clone VAE-LSTM-for-anomaly-detection

Clone via HTTPS

git clone https://github.com/lin-shuyu/VAE-LSTM-for-anomaly-detection.git

Clone via SSH

[email protected]:lin-shuyu/VAE-LSTM-for-anomaly-detection.git

Download ZIP

Download master.zip

Found an issue?

Report bugs or request features on the VAE-LSTM-for-anomaly-detection issue tracker:

Open GitHub Issues

Similar to VAE-LSTM-for-anomaly-detection

gold-miner tensorflow keras TensorFlow-Examples data-science-ipython-notebooks machine-learning-curriculum handson-ml tflearn EffectiveTensorflow TensorFlow-Tutorials TensorLayer seq2seq onnx tutorials TensorFlow-World tensorflow_cookbook tensorflow-nlp darkflow sketch-code deepo faceai gocv object_detector_app ChosunTruck lambda-packs TensorFlow-Book DeepSpeech Mask_RCNN stanford-tensorflow-tutorials facenet