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cs.LG2025
Joint Embedding vs Reconstruction: Provable Benefits of Latent Space Prediction for Self Supervised Learning
Hugues Van Assel, Mark Ibrahim, Tommaso Biancalani +2
Reconstruction and joint embedding have emerged as two leading paradigms in Self Supervised Learning (SSL). Reconstruction methods focus on recovering the original sample from a di…
cs.LG2024
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?
Mark Ibrahim, David Klindt, Randall Balestriero
Deep Learning is often depicted as a trio of data-architecture-loss. Yet, recent Self Supervised Learning (SSL) solutions have introduced numerous additional design choices, e.g.,…