HyperAIHyperAI

Command Palette

Search for a command to run...

Console

Semi Supervised Image Classification On Cifar 6

Metrics

Percentage error

Results

Performance results of various models on this benchmark

Paper Title
Ⅱ-Model53.12Temporal Ensembling for Semi-Supervised Learning
MixUp47.43mixup: Beyond Empirical Risk Minimization
MeanTeacher47.32Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
VAT36.03Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning
LiDAM19.17LiDAM: Semi-Supervised Learning with Localized Domain Adaptation and Iterative Matching
MixMatch11.08MixMatch: A Holistic Approach to Semi-Supervised Learning
RealMix9.79RealMix: Towards Realistic Semi-Supervised Deep Learning Algorithms
EnAET7.6RealMix: Towards Realistic Semi-Supervised Deep Learning Algorithms
ReMixMatch6.27ReMixMatch: Semi-Supervised Learning with Distribution Alignment and Augmentation Anchoring
DoubleMatch5.56±0.42DoubleMatch: Improving Semi-Supervised Learning with Self-Supervision
Semi-MMDC5.51±0.25Boosting the Performance of Semi-Supervised Learning with Unsupervised Clustering
FixMatch (CTA)5.07±0.33FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
FixMatch+CR5.04Contrastive Regularization for Semi-Supervised Learning
FreeMatch4.88FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning
NP-Match4.87NP-Match: When Neural Processes meet Semi-Supervised Learning
SelfMatch4.87±0.26SelfMatch: Combining Contrastive Self-Supervision and Consistency for Semi-Supervised Learning
SimMatch4.84SimMatch: Semi-supervised Learning with Similarity Matching
FlexMatch4.8±0.06FlexMatch: Boosting Semi-Supervised Learning with Curriculum Pseudo Labeling
DP-SSL4.78±0.26DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples
FixMatch+DM4.77±0.09-
0 of 24 row(s) selected.
Semi Supervised Image Classification On Cifar 6 | SOTA | HyperAI