Representation Learning (Similarity-Based) — Metric Learning, Contrastive, InfoNCE | MIT 6.7960 Lecture 12
Similarity-based representation learning does not reconstruct input; it directly shapes latent geometry: pull same-class representations together, push different ones apart. InfoNCE turns this into 'spot the positive among negatives', and alignment / uniformity give it interpretable metrics.