11 citations · 21 across the 12 of their papers we have counts for
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cs.LG2023★ 11 cited
ContraNorm: A Contrastive Learning Perspective on Oversmoothing and Beyond
Xiaojun Guo, Yifei Wang, Tianqi Du +1
Oversmoothing is a common phenomenon in a wide range of Graph Neural Networks (GNNs) and Transformers, where performance worsens as the number of layers increases. Instead of chara…
cs.LG2023
A Message Passing Perspective on Learning Dynamics of Contrastive Learning
Yifei Wang, Qi Zhang, Tianqi Du +3
In recent years, contrastive learning achieves impressive results on self-supervised visual representation learning, but there still lacks a rigorous understanding of its learning…
cs.LG2023★ 2 cited
ArCL: Enhancing Contrastive Learning with Augmentation-Robust Representations
Xuyang Zhao, Tianqi Du, Yisen Wang +2
Self-Supervised Learning (SSL) is a paradigm that leverages unlabeled data for model training. Empirical studies show that SSL can achieve promising performance in distribution shi…