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fMNIST

Benchmarks

Task NameDataset NameSOTA ResultTrend
ClassificationFMNIST (test)
Accuracy99.06
149
Dimensionality ReductionFMNIST
AUC R_NX Score76.48
42
Image ClassificationFMNIST
Accuracy (IID)84.842
33
ClassificationFMNIST
Accuracy83.3
33
ClusteringFMNIST
NMI66.35
31
Anomaly DetectionFMNIST
Avg AUROC0.956
29
Image ClassificationFMNIST
Speedup69.24
21
Dimensionality ReductionFMNIST
AUC RNX0.7648
21
KNN ClassificationFMNIST
Accuracy (k=1)87.47
20
Silhouette Score EvaluationFMNIST
Silhouette Score0.2315
20
KNN ClassificationFMNIST
Accuracy (k=5)88.3
20
OOD DetectionFMNIST In-distribution: CIFAR100 (test)
AUPR (%)78.6
18
OOD DetectionFMNIST In-distribution: CIFAR10 (test)
AUPR92.5
18
Untargeted white-box adversarial attackFMNIST original (test)
Original Error Rate0.1
16
Image ClassificationFMNIST i.i.d. (test)
Accuracy75.81
14
Image ClassificationFMNIST
Accuracy86.7
13
Out-of-Distribution DetectionFMNIST
OOD Score97.3
13
Feature AttributionFMNIST
INFD0
13
Image ClassificationFMNIST
Communication Cost (GB)0.001
12
Image ClassificationFMNIST label shift (test)
Top-1 Accuracy72.66
12
Image ReconstructionfMNIST (test)
MSE (Reconstruction Error)0.0054
11
Image ClassificationFMNIST
NLL0.47
10
Image ClassificationFMNIST
Runtime1.67
10
Image ClassificationFMNIST non-i.i.d. (test)
Accuracy (Test)70.83
10
Subset SelectionFMNIST (train)
Speedup69.24
10
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