Semi-supervised classification

Benchmarks

Dataset Name	SOTA Method	Metric
ADNI CN vs. AD (90% test)	GAT	Accuracy79.1	40	8d ago
MNIST digits 8, 9 n=10000 (unlabeled points)		Average Run Time (s)0.01	25	3mo ago
NIFD (10% train, 90% test)	ARMA-C3	Accuracy72.3	20	8d ago
ADNI CN vs. MCI (10% train, 90% test)	ARMA	Accuracy81.5	20	8d ago
MedMNIST Breast (10% train 90% test)	ARMA	Accuracy85.7	20	8d ago
tieredImageNet (test)	TPN-semi	Accuracy71.01	16	3mo ago
MNIST 100 labels	ADGM	Error Rate0.0096	16	3mo ago
SVHN 1000 labels	ADGM	Error Rate16.61	14	3mo ago
ImageNet 10% labels (train)	TWIST	Top-1 Accuracy0.765	12	3mo ago
ImageNet 1% labels (train)	TWIST	Top-1 Acc69.6	12	3mo ago
Reuters	MGCN-FLC	Accuracy99.1	10	2mo ago
ProteinFold	MGCN-FLC	Accuracy60	10	2mo ago
NGs	MGCN-FLC	Accuracy97.8	10	2mo ago
BBCSports	MGCN-FLC	Accuracy97.4	10	2mo ago
WebKB	MGCN-FLC	Accuracy91.8	10	2mo ago
NUS-WIDE	MGCN-FLC	Accuracy99	10	2mo ago
MNIST		Accuracy98	10	2mo ago
Caltech101 7	MGCN-FLC	Accuracy97.5	10	2mo ago
BBCnews	MGCN-FLC	Accuracy0.984	10	2mo ago
ImageNet 10% labels 1K (val)	LEWEL_B	Top-5 Acc90.1	10	3mo ago
ImageNet 1% labels 1K (val)	LEWEL_B	Top-5 Accuracy83.2	10	3mo ago
ImageNet 10% labels	BYOL	Top-1 Acc77.7	10	3mo ago
MNIST 100 labels statically binarized (test)	SSLGAN	Error Rate (%)0.8	10	3mo ago
MNIST 1000 labels	Ladder Networks	Error Rate0.0084	8	3mo ago
STL-10 25 labels per class	UniMatch V2	Accuracy (Seed 0)91.7	4	3mo ago

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