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Models/IF

IF

Reported on 19 benchmarks across 8 tasks · 1 paper

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Computer Vision11 results

  • Unsupervised Anomaly Detection with Specified Settings -- 20% anomalyonCats and Dogs
    AUC-ROC
    0.706
    best: 0.953 (Shell-Renormalized)
  • Unsupervised Anomaly Detection with Specified Settings -- 20% anomalyonFashion-MNIST
    AUC-ROC
    0.889
  • Unsupervised Anomaly Detection with Specified Settings -- 30% anomalyonCIFAR-10
    AUC-ROC
    0.661
    best: 0.894 (Shell-Renormalized)
  • Unsupervised Anomaly Detection with Specified Settings -- 30% anomalyonFashion-MNIST
    AUC-ROC
    0.889
  • Unsupervised Anomaly Detection with Specified Settings -- 30% anomalyonMNIST
    AUC-ROC
    0.797
    best: 0.904 (LVAD)
  • Unsupervised Anomaly Detection with Specified Settings -- 1% anomalyonCats and Dogs
    AUC-ROC
    0.878
    best: 0.981 (RSRAE)
  • Unsupervised Anomaly Detection with Specified Settings -- 10% anomalyonFashion-MNIST
    AUC-ROC
    0.915
  • Unsupervised Anomaly Detection with Specified Settings -- 10% anomalyonCIFAR-10
    AUC-ROC
    0.786
    best: 0.903 (LVAD)
  • Unsupervised Anomaly Detection with Specified Settings -- 10% anomalyonMNIST
    AUC-ROC
    0.821
    best: 0.938 (LVAD)
  • Unsupervised Anomaly Detection with Specified Settings -- 10% anomalyonSTL-10
    AUC-ROC
    0.797
    best: 0.997 (Shell-Renormalized)
  • Unsupervised Anomaly Detection with Specified Settings -- 10% anomalyonCats and Dogs
    AUC-ROC
    0.798
    best: 0.996 (Shell-Renormalized)

Methodology3 results

  • Anomaly DetectiononCIFAR-10
    AUC-ROC
    0.661
    best: 0.894 (Shell-Renormalized)
  • Anomaly DetectiononFashion-MNIST
    AUC-ROC
    0.889
  • Anomaly DetectiononMNIST
    AUC-ROC
    0.797
    best: 0.904 (LVAD)

Graphs3 results

  • Unsupervised Anomaly DetectiononCIFAR-10
    AUC-ROC
    0.661
    best: 0.894 (Shell-Renormalized)
  • Unsupervised Anomaly DetectiononFashion-MNIST
    AUC-ROC
    0.889
  • Unsupervised Anomaly DetectiononMNIST
    AUC-ROC
    0.797
    best: 0.904 (LVAD)

Time Series2 results

  • Time Series AnalysisonUCR Anomaly Archive
    accuracy· 2023-11-21
    0.376
    best: 0.708 (TimeVQVAE-AD)
    Explainable Time Series Anomaly Detection using Masked Latent Generative ModelingarXiv:2311.12550
  • Time Series Anomaly DetectiononUCR Anomaly Archive
    accuracy· 2023-11-21
    0.376
    best: 0.708 (TimeVQVAE-AD)
    Explainable Time Series Anomaly Detection using Masked Latent Generative ModelingarXiv:2311.12550