Anomaly Detection On Fashion Mnist
Metrics
ROC AUC
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | ROC AUC |
|---|---|
| panda-adapting-pretrained-features-for | 84.8 |
| p-kdgan-progressive-knowledge-distillation | 0.9293 |
| unsupervised-anomaly-detection-and | 92.01 |
| panda-adapting-pretrained-features-for | 92.8 |
| gan-based-anomaly-detection-in-imbalance | 98.6 |
| shell-theory-a-statistical-model-of-reality | 92.1 |
| unsupervised-anomaly-detection-and | 93.57 |
| panda-adapting-pretrained-features-for | 91.8 |
| anomaly-detection-via-reverse-distillation | 95.0 |
| panda-adapting-pretrained-features-for | 95.6 |
| unsupervised-anomaly-detection-and | 94.41 |
| dasvdd-deep-autoencoding-support-vector-data | 92.6 |