DeepAnT

Original Paper

DeepAnT: A Deep Learning Approach for Unsupervised Anomaly Detection in Time Series

Original Authors

(Deutsches Forschungszentrum für Künstliche Intelligenz)

• Mohsin Munir
• Shoaib Ahmed Siddiqui
• Andreas Dengel
• Sheraz Ahmed

Main notebooks

• deepant_vs_lstm.ipynb
  • This gives F-score comparison between the DeepAnT and LSTM models
• sarima.ipynb
  • Shows the performance of ARIMA on the same dataset
• FlashCrash.ipynb
  • Shows the performance of DeepAnT around the Flash Crash

Helper notebooks

• outlier_synthesis.ipynb
  • Generates synthetic outliers in time-series data from yfinance

Initial notebooks

• deepant.ipynb
  • Initial implementation of DeepAnT
• lstm.ipynb
  • Initial implementation of DeepAnT
• deepant_multi_file.ipynb
  • Initial notebook to run DeepAnT for multiple files in same notebook and give tabulr output