
VAE-LSTM-for-anomaly-detection
by lin-shuyu (personal account)
We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series. (description from the project’s GitHub page)
Repository facts
- Stars
- 578
- Forks
- 95
- Open issues and pull requests
- 13
- Primary language
- Jupyter Notebook
- License
- No license file detected
- Owner
- lin-shuyu · Personal account
- Created
- Feb 13, 2020
- Last push
- Nov 21, 2022
Topics
Related projects
Projects that share this one’s GitHub topics.
Rank 5,440: altosaar/variational-autoencoder
Variational autoencoder implemented in tensorflow and pytorch (including inverse autoregressive flow)
1,193 starsPythonMITLast push Apr 24, 2024
Rank 817: yzhao062/pyod
A Python library for anomaly detection across tabular, time series, graph, text, image, and audio data. 60+ detectors, benchmark-backed ADEngine orchestration, and an agentic work…
10,046 starsPythonBSD-2-ClauseLast push Oct 12, 2026
Rank 5,416: khundman/telemanom
A framework for using LSTMs to detect anomalies in multivariate time series data. Includes spacecraft anomaly data and experiments from the Mars Science Laboratory and SMAP missio…
1,201 starsJupyter NotebookOther licenseLast push Jan 17, 2025
Rank 8,524: KDD-OpenSource/DeepADoTS
Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
601 starsPythonMITLast push Apr 13, 2026
Rank 7,704: aapatel09/handson-unsupervised-learning
Code for Hands-on Unsupervised Learning Using Python (O'Reilly Media)
706 starsJupyter NotebookNo license file detectedLast push Mar 1, 2026
Rank 5,452: RubensZimbres/Repo-2017
My first Python repo with codes in Machine Learning, NLP and Deep Learning with Keras and Theano
1,191 starsPythonNo license file detectedLast push Dec 6, 2021