https://github.com/hendrycks/outlier-exposure

Deep Anomaly Detection with Outlier Exposure (ICLR 2019)
https://github.com/hendrycks/outlier-exposure

anomaly anomaly-detection calibration deep-learning ml-safety out-of-distribution-detection pytorch

Last synced: 19 days ago
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Deep Anomaly Detection with Outlier Exposure (ICLR 2019)

• Host: GitHub
• URL: https://github.com/hendrycks/outlier-exposure
• Owner: hendrycks
• License: apache-2.0
• Created: 2018-05-22T22:22:24.000Z (almost 7 years ago)
• Default Branch: master
• Last Pushed: 2021-10-09T01:31:17.000Z (over 3 years ago)
• Last Synced: 2025-03-29T06:03:50.907Z (26 days ago)
• Topics: anomaly, anomaly-detection, calibration, deep-learning, ml-safety, out-of-distribution-detection, pytorch
• Language: Python
• Homepage:
• Size: 360 MB
• Stars: 556
• Watchers: 18
• Forks: 107
• Open Issues: 5
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-production-machine-learning - Deep Anomaly Detection with Outlier Exposure - exposure.svg?style=social) - Outlier Exposure (OE) is a method for improving anomaly detection performance in deep learning models. [Paper](https://arxiv.org/pdf/1812.04606.pdf) (Industry-strength AD)