Contrastive learning involves creating an embedding space by comparing related and unrelated samples, such as images of a cat and dog versus a banana. This method emphasizes the importance of positive and negative examples to train networks effectively. Energy-based models provide a framework for understanding these concepts, as illustrated by a detailed explanation from a key figure in the field.
