An Empirical Study of Self-supervised Learning with Wasserstein Distance

no code implementations • 16 Oct 2023 • Makoto Yamada, Yuki Takezawa, Guillaume Houry, Kira Michaela Dusterwald, Deborah Sulem, Han Zhao, Yao-Hung Hubert Tsai

We find that the model performance depends on the combination of TWD and probability model, and that the Jeffrey divergence regularization helps in model training.

Representation Learning Self-Supervised Learning