A list of Papers on anomaly detection.
- Isolation Forest - ICDM 2008
- Extended Isolation Forest -This paper is hard to follow yet some idea are good.
- LOF: Identifying Density-Based Local Outliers -SIGMOD 2000 A locally density based method.
- Variational Autoencoder based Anomaly Detection using Reconstruction Probability Most Auto-encoder methods use either reconstruction error or negative log-likelihood, this is novel. This has been used by Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications in Application section.
- DEEP AUTOENCODING GAUSSIAN MIXTURE MODEL FOR UNSUPERVISED ANOMALY DETECTION ICLR 2018, experiments done on KDDCUP
- Deep Anomaly Detection with Outlier Exposure Rejected by ICLR2019, but i personally think this is a good paper.
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Long short term memory networks for anmomaly detection in time series
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LSTM-based Encoder-Decoder for Multi-sensor Anomaly Detection - ICML 2016 Workshop. Multivariate Guassian distribution based.
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A Multimodel Anomaly Detector for Robot-Assisted Feeding Using an LSTM-based Variational Autoencoder - IEEE Robotics and Automation Letters 2018.
- One-Class SVMs for Document Classification -JMLR 2001
- Support Vector Data Description
- Deep One-Class Classification - ICML 2018 Oral. A well written paper, sold a excellent story.
- Incorporating Feedback into Tree-based Anomaly Detection - KDD 2017 Workshop on Interactive Data Exploration and Analytics. Modifications are made on the basis of Isolation Forest.
- Feedback-Guided Anomaly Discovery via Online Optimization - KDD 2018. An improved version of "Incorporating Feedback into Tree-based Anomaly Detection"
- Unsupervised Anomaly Detection via Variational Auto-Encoder for Seasonal KPIs in Web Applications -WWW2018
- [DeepLog]