Contrastive Learning

Contrastive learning is a deep learning technique used for unsupervised representation learning. Its goal is to learn representations of data such that similar instances are close to each other in the representation space, while dissimilar instances are further apart. This method has shown excellent performance in tasks such as image retrieval, zero-shot learning, and cross-modal retrieval, with the learned representations serving as features for downstream tasks like classification and clustering.