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Semi Supervised Image Classification On Cifar 7

Métriques

Percentage error

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Percentage error	Paper Title	Repository
PCL	5.88±1.19	Probabilistic Contrastive Learning for Domain Adaptation
NP-Match	4.91	NP-Match: When Neural Processes meet Semi-Supervised Learning
RelationMatch	4.96	RelationMatch: Matching In-batch Relationships for Semi-supervised Learning
FlexMatch	4.99±0.16	FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
FixMatch (CTA)	11.39±3.35	FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
ReMixMatch	19.10	ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring	-
Semi-MMDC	7.39±0.61	Boosting the Performance of Semi-Supervised Learning with Unsupervised Clustering
SelfMatch	6.81±1.08	SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning	-
DoubleMatch	13.59±5.60	DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision
MutexMatch (k=0.6C)	5.79	MutexMatch: Semi-Supervised Learning with Mutex-Based Consistency Regularization
SimMatch	5.6	SimMatch: Semi-supervised Learning with Similarity Matching
DP-SSL	6.54±0.98	DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples	-
DebiasPL (w/ FixMatch)	5.4	Debiased Learning from Naturally Imbalanced Pseudo-Labels
FreeMatch	4.9	FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
ShrinkMatch	5.08	Shrinking Class Space for Enhanced Certainty in Semi-Supervised Learning
UL-Hopfield (ULH)	16.90	Unsupervised Learning using Pretrained CNN and Associative Memory Bank	-
FixMatch+CR	5.69	Contrastive Regularization for Semi-Supervised Learning	-
CoMatch (w. SimCLR)	6.91±1.39	CoMatch: Semi-supervised Learning with Contrastive Graph Regularization

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