NP-Match: When Neural Processes meet Semi-Supervised Learning

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Benchmark Model Rank Results
semi-supervised-image-classification-on-cifar-10-250-labelsNP-Match#6Percentage error: 4.87
semi-supervised-image-classification-on-cifar-10-40-labelsNP-Match#3Percentage error: 4.91
semi-supervised-image-classification-on-cifar-10-4000-labelsNP-Match#5Percentage error: 4.11±0.02
semi-supervised-image-classification-on-cifar-10-4000-labelsUPS (wrn-28-2)#8Percentage error: 4.25
semi-supervised-image-classification-on-cifar-100-10000-labelsNP-Match#4Percentage error: 21.22
semi-supervised-image-classification-on-cifar-100-2500-labelsNP-Match#5Percentage error: 26.03
semi-supervised-image-classification-on-cifar-100-400-labelsNP-Match#8Percentage error: 38.67
semi-supervised-image-classification-on-imagenet-10-labeled-dataNP-Match(ResNet-50)#42Top 1 Accuracy: 58.22%
semi-supervised-image-classification-on-stl-10-1000-labelsNP-Match#4Accuracy: 94.53
semi-supervised-image-classification-on-stl-10-40-labelsNP-Match#4Accuracy: 85.8

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