Data2Vec (self-supervised learning across modalities)
Data2Vec is a self-supervised learning framework that enables learning across different modalities such as text, speech, and images, enhancing AI model adaptability.
Self-Supervised Learning
SwAV (swapping assignments between views)
SwAV is a self-supervised learning method in computer vision that enables effective learning by swapping assignments between different views of data.
Self-supervised learning
Self-supervised learning is a machine learning paradigm that uses unlabeled data to train models, allowing them to learn useful representations without extensive human annotation.
SimCLR (simple framework for contrastive learning)
SimCLR is a framework for contrastive learning that utilizes deep learning techniques to train models without labeled data. It focuses on maximizing agreement between differently augmented views of the same data.
MAE (masked autoencoder for vision)
MAE is a framework for self-supervised learning in computer vision, focusing on reconstructing masked portions of images.