Unsupervised Data Augmentation for Consistency Training

Citation edge evidence

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• A Simple Framework for Contrastive Learning of Visual Representations→Unsupervised Data Augmentation for Consistency TrainingLegacy edge — source detail unavailable
• Emerging Properties in Self-Supervised Vision Transformers→Unsupervised Data Augmentation for Consistency TrainingLegacy edge — source detail unavailable
• Language Models are Few-Shot Learners→Unsupervised Data Augmentation for Consistency TrainingLegacy edge — source detail unavailable
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence→Unsupervised Data Augmentation for Consistency TrainingLegacy edge — source detail unavailable
• Longformer: The Long-Document Transformer→Unsupervised Data Augmentation for Consistency TrainingLegacy edge — source detail unavailable
• XLNet: Generalized Autoregressive Pretraining for Language Understanding→Unsupervised Data Augmentation for Consistency TrainingLegacy edge — source detail unavailable
• Text Data Augmentation for Deep Learning→Unsupervised Data Augmentation for Consistency TrainingLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Glove: Global Vectors for Word RepresentationLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Xception: Deep Learning with Depthwise Separable ConvolutionsLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Distributed Representations of Words and Phrases and their CompositionalityLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Semi-Supervised Classification with Graph Convolutional NetworksLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Attention Is All You NeedLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→mixup: Beyond Empirical Risk MinimizationLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→SpecAugment: A Simple Data Augmentation Method for Automatic Speech RecognitionLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Learning Word Vectors for Sentiment AnalysisLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised …Legacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]Legacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
• Unsupervised Data Augmentation for Consistency Training→Deep Speech: Scaling up end-to-end speech recognitionLegacy edge — source detail unavailable
• Learning Word Vectors for Sentiment Analysis→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Distributed Representations of Words and Phrases and their Compositionality→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Glove: Global Vectors for Word Representation→A unified architecture for natural language processingLegacy edge — source detail unavailable
• Glove: Global Vectors for Word Representation→Distributed Representations of Words and Phrases and their CompositionalityLegacy edge — source detail unavailable
• Xception: Deep Learning with Depthwise Separable Convolutions→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
• Deep Contextualized Word Representations→Glove: Global Vectors for Word RepresentationLegacy edge — source detail unavailable
• SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition→Deep Speech: Scaling up end-to-end speech recognitionLegacy edge — source detail unavailable
• XLNet: Generalized Autoregressive Pretraining for Language Understanding→Deep Contextualized Word RepresentationsLegacy edge — source detail unavailable
• XLNet: Generalized Autoregressive Pretraining for Language Understanding→BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingLegacy edge — source detail unavailable
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding→A unified architecture for natural language processingLegacy edge — source detail unavailable
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding→Distributed Representations of Words and Phrases and their CompositionalityLegacy edge — source detail unavailable
• BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding→Glove: Global Vectors for Word RepresentationLegacy edge — source detail unavailable
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence→mixup: Beyond Empirical Risk MinimizationLegacy edge — source detail unavailable
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence→SpecAugment: A Simple Data Augmentation Method for Automatic Speech RecognitionLegacy edge — source detail unavailable
• FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence→Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised …Legacy edge — source detail unavailable
• A Simple Framework for Contrastive Learning of Visual Representations→FixMatch: Simplifying Semi-Supervised Learning with Consistency and ConfidenceLegacy edge — source detail unavailable
• Longformer: The Long-Document Transformer→Learning Word Vectors for Sentiment AnalysisLegacy edge — source detail unavailable
• Longformer: The Long-Document Transformer→BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingLegacy edge — source detail unavailable
• Language Models are Few-Shot Learners→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
• Language Models are Few-Shot Learners→Glove: Global Vectors for Word RepresentationLegacy edge — source detail unavailable
• Language Models are Few-Shot Learners→[No title in the source record — Edinburgh Research Explorer (University of Edinburgh)]Legacy edge — source detail unavailable
• Language Models are Few-Shot Learners→BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingLegacy edge — source detail unavailable
• Emerging Properties in Self-Supervised Vision Transformers→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
• Emerging Properties in Self-Supervised Vision Transformers→BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingLegacy edge — source detail unavailable
• Emerging Properties in Self-Supervised Vision Transformers→A Simple Framework for Contrastive Learning of Visual RepresentationsLegacy edge — source detail unavailable
• Text Data Augmentation for Deep Learning→Distilling the Knowledge in a Neural NetworkLegacy edge — source detail unavailable
• Text Data Augmentation for Deep Learning→BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingLegacy edge — source detail unavailable
• Text Data Augmentation for Deep Learning→A Simple Framework for Contrastive Learning of Visual RepresentationsLegacy edge — source detail unavailable