F-MNIST
Benchmarks
| Task Name | Dataset Name | SOTA Result | Trend | |
|---|---|---|---|---|
| Image Classification | F-MNIST (test) | Accuracy97.62 | 156 | |
| Image Classification | F-MNIST | Accuracy92.8 | 139 | |
| Backdoor Attack | F-MNIST | ASR97.81 | 25 | |
| Conformal Prediction | F-MNIST | Average Prediction Set Size1.7 | 24 | |
| INR classification | F-MNIST Implicit Neural Representations (test) | Accuracy84.6 | 21 | |
| Differentially Private Image Synthesis | F-MNIST | FID11.6 | 16 | |
| Image Classification | F-MNIST NIID, κ=1 | Accuracy74.89 | 12 | |
| Image Classification | F-MNIST Uniform | Accuracy84.45 | 12 | |
| Image Classification | F-MNIST IDN-50% (test) | Accuracy76.43 | 12 | |
| Image Classification | F-MNIST IDN-40% (test) | Accuracy85.81 | 12 | |
| Image Classification | F-MNIST IDN-30% (test) | Accuracy89.61 | 12 | |
| Image Classification | F-MNIST IDN-20% (test) | Accuracy90.83 | 12 | |
| Image Classification | F-MNIST IDN-10% (test) | Accuracy91.96 | 12 | |
| One-class classification | f-MNIST (test) | AUC95.8 | 12 | |
| Dimensionality Reduction | F-MNIST | Triplet Centroid Accuracy92.5 | 10 | |
| Dimensionality Reduction | F-MNIST (test) | Class Angular Distortion Index0.0207 | 8 | |
| Semantic Communication Backdoor Attack | F-MNIST standard (test) | Attack Success Rate (ASR)99.98 | 7 | |
| Classification under DBA attack | F-MNIST | Balance Accuracy96.74 | 7 | |
| Image Classification | F-MNIST 1000x1 | Accuracy83 | 6 | |
| Image Classification | F-MNIST 500x2 | Final Accuracy83.9 | 6 | |
| Accuracy Prediction | F-MNIST (test) | MSE2.94 | 6 | |
| Model Stealing | F-MNIST | Agreement69.6 | 6 | |
| Image Classification | F-MNIST Dirichlet | Final Accuracy (%)86.4 | 5 | |
| Classification | F-MNIST unlabeled 2 (train) | Accuracy96 | 5 | |
| Classification | F-MNIST unlabeled 1 (train) | Accuracy95.41 | 5 |
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