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Papers Benchmarks Datasets Tasks

MNIST dataset and benchmarks – Page 8 · SOTA2 Research

Research Datasets

MNIST

Benchmarks

Task NameDataset NameSOTA MethodSort

Task NameDataset NameSOTA ResultTrendResults

MNIST 6Classes

82.7Accuracy

24

MNIST 3-class

94.53Accuracy

24

MNIST 8Classes

80.1Accuracy

24

MNIST 4-class

87.82Accuracy

24

MNIST 9Classes

77.13Accuracy

24

Certified Robustness

MNIST

99.2Certified Accuracy (R=0.00)

24

Model Extraction

MNIST

55.1Fidelity

24

Image Classification

MNIST (test)

94.61Accuracy

24

Input Discrimination

MNIST DeepGini subsets

0.021Gini Impurity

24

Gradient Inversion Attack

MNIST

0.018MSE

24

MNIST

86NMI

24

MNIST (test)

0.406Bits/dim

24

Adversarial Attack

MNIST (test)

100ASR

24

Task Predictive Performance

MNIST-Add-Incomp (test)

94.99Accuracy/AUC

24

RCF-MNIST

0.146RMSE (Avg)

24

Image Classification

MNIST Permutation-invariant (DW)

98.64Accuracy

24

Image Classification

Permutation-invariant MNIST (SW)

98.2Accuracy

24

Image Classification

MNIST Split

99.69Test Accuracy

24

Binary Classification

MNIST 0 and 1 (test)

100Certification Rate

24

Image Classification

MNIST

99.8Accuracy

23

MNIST+#

96.88Accuracy

22

Continual Learning

MNIST Shuffled Labels

97.6Accuracy (ACC)

22

Clustering Evaluation

MNIST 10,000 random samples

44Jaccard Index

22

Category Unlearning

MNIST (test)

99.06Accuracy (Dr)

22

Full-class forgetting

MNIST (retain)

85.5Accuracy

22

Page 8 of 59

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