Paper

Unsupervised Data Augmentation for Consistency Training

Semi-supervised learning lately has shown much promise in improving deep learning models when labeled data is scarce. Common among recent approaches is the use of consistency training on a large amount of unlabeled data to constrain model predictions to be invariant to input noise... (read more)

Results in Papers With Code
(↓ scroll down to see all results)