MIT's Sitzmann: Representation learning lacks a theory of what it converges to
vincesitzmann · x · 2026-10-20
MIT's Vince Sitzmann argues that since contrastive learning, representation learning has remained somewhat alchemical: a proper theory describing what representations actually converge to is still missing. As a result, training objectives are hard to interpret — methods like DINO and JEPA work well, but their objectives remain close to "black magic."
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