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Models/InstanceGM-SS

InstanceGM-SS

Reported on 12 benchmarks across 2 tasks · 1 paper · 3 SOTA

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

Computer Vision8 results

  • Image ClassificationonRed MiniImageNet 60% label noise
    Accuracy· 2022-09-02
    53.21
    SOTA
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Image ClassificationonRed MiniImageNet 60% label noise
    Test Accuracy· 2022-09-02
    53.21
    SOTA
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Image ClassificationonRed MiniImageNet 20% label noise
    Accuracy· 2022-09-02
    60.89
    best: 69 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Image ClassificationonRed MiniImageNet 40% label noise
    Accuracy· 2022-09-02
    56.37
    best: 64.6 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Image ClassificationonRed MiniImageNet 80% label noise
    Accuracy· 2022-09-02
    44.03
    best: 51.2 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Image ClassificationonRed MiniImageNet 80% label noise
    Test Accuracy· 2022-09-02
    44.03
    best: 51.2 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Image ClassificationonRed MiniImageNet 40% label noise
    Test Accuracy· 2022-09-02
    56.37
    best: 64.6 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Image ClassificationonRed MiniImageNet 20% label noise
    Test Accuracy· 2022-09-02
    60.89
    best: 69 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906

Medical4 results

  • Document Text ClassificationonRed MiniImageNet 60% label noise
    Test Accuracy· 2022-09-02
    53.21
    SOTA
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Document Text ClassificationonRed MiniImageNet 80% label noise
    Test Accuracy· 2022-09-02
    44.03
    best: 51.2 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Document Text ClassificationonRed MiniImageNet 40% label noise
    Test Accuracy· 2022-09-02
    56.37
    best: 64.6 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906
  • Document Text ClassificationonRed MiniImageNet 20% label noise
    Test Accuracy· 2022-09-02
    60.89
    best: 69 (NCR (ResNet-18))
    Instance-Dependent Noisy Label Learning via Graphical ModellingarXiv:2209.00906