Artificial Intelligence | AI on Instagram: "Contrastive learning is a type of self-supervised learning where the goal is to learn representations by comparing pairs of data. Instead of predicting missing parts of data like other self-supervised algorithms, it teaches a model to bring similar examples (called positive pairs) closer in the embedding space while spacing different ones (called negative pairs) farther apart. For instance, two different versions of the same image (rotated and cropped)

Heat Kernel Driven Dual-Stage Hard Sample Aware Contrastive Learning for Graph Clustering | Proceedings of the 1st International Workshop on Multi-Sensorial Media and Applications

Supervised vs. Unsupervised Learning: Explained

Supervised Learning

What Is Self-Supervised Learning? | IBM