Semi-supervised classification

Benchmarks

Dataset Name	SOTA Method	Metric
ADNI CN vs. AD (90% test)	GAT	Accuracy79.1	40	2mo ago
MNIST digits 8, 9 n=10000 (unlabeled points)		Average Run Time (s)0.01	25	4mo ago
NIFD (10% train, 90% test)	ARMA-C3	Accuracy72.3	20	2mo ago
ADNI CN vs. MCI (10% train, 90% test)	ARMA	Accuracy81.5	20	2mo ago
MedMNIST Breast (10% train 90% test)	ARMA	Accuracy85.7	20	2mo ago
tieredImageNet (test)	TPN-semi	Accuracy71.01	16	4mo ago
MNIST 100 labels	ADGM	Error Rate0.0096	16	4mo ago
SVHN 1000 labels	ADGM	Error Rate16.61	14	4mo ago
ImageNet 10% labels (train)	TWIST	Top-1 Accuracy0.765	12	4mo ago
ImageNet 1% labels (train)	TWIST	Top-1 Acc69.6	12	4mo ago
Reuters	MGCN-FLC	Accuracy99.1	10	3mo ago
ProteinFold	MGCN-FLC	Accuracy60	10	3mo ago
NGs	MGCN-FLC	Accuracy97.8	10	3mo ago
BBCSports	MGCN-FLC	Accuracy97.4	10	3mo ago
WebKB	MGCN-FLC	Accuracy91.8	10	3mo ago
NUS-WIDE	MGCN-FLC	Accuracy99	10	3mo ago
MNIST		Accuracy98	10	3mo ago
Caltech101 7	MGCN-FLC	Accuracy97.5	10	3mo ago
BBCnews	MGCN-FLC	Accuracy0.984	10	3mo ago
ImageNet 10% labels 1K (val)	LEWEL_B	Top-5 Acc90.1	10	4mo ago
ImageNet 1% labels 1K (val)	LEWEL_B	Top-5 Accuracy83.2	10	4mo ago
ImageNet 10% labels	BYOL	Top-1 Acc77.7	10	4mo ago
MNIST 100 labels statically binarized (test)	SSLGAN	Error Rate (%)0.8	10	4mo ago
ECG 20% labels	CaTT	Accuracy77.43	9	1mo ago
ECG 10% labels	CaTT	Accuracy73.84	9	1mo ago

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