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Zeyu Yun

2 accepted papers

2025

URLOST: Unsupervised Representation Learning without Stationarity or Topology

ICLR 2025poster

Unsupervised representation learning has seen tremendous progress. However, it is constrained by its reliance on domain specific stationarity and topology, a limitation not found in biological intelligence systems. For instance, unlike computer vision, human vision can process visual signals sampled…

Cited by 1SourcePDFScholar
2023

Minimalistic Unsupervised Representation Learning with the Sparse Manifold Transform

ICLR 2023top-25%

We describe a minimalistic and interpretable method for unsupervised representation learning that does not require data augmentation, hyperparameter tuning, or other engineering designs, but nonetheless achieves performance close to the state-of-the-art (SOTA) SSL methods. Our approach leverages the…

Cited by 8SourcePDFScholar