11 citations · 17 across the 3 of their papers we have counts for
3 papers
cs.CV2024
Revisiting Disentanglement in Downstream Tasks: A Study on Its Necessity for Abstract Visual Reasoning
Ruiqian Nai, Zixin Wen, Ji Li +2
In representation learning, a disentangled representation is highly desirable as it encodes generative factors of data in a separable and compact pattern. Researchers have advocate…
cs.LG2022★ 6 cited
The Mechanism of Prediction Head in Non-contrastive Self-supervised Learning
Zixin Wen, Yuanzhi Li
Recently the surprising discovery of the Bootstrap Your Own Latent (BYOL) method by Grill et al. shows the negative term in contrastive loss can be removed if we add the so-called…
cs.LG2021★ 11 cited
Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
Zixin Wen, Yuanzhi Li
How can neural networks trained by contrastive learning extract features from the unlabeled data? Why does contrastive learning usually need much stronger data augmentations than s…