The following publications are possibly variants of this publication:
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- What's Behind the Mask: Understanding Masked Graph Modeling for Graph AutoencodersJintang Li, Ruofan Wu, Wangbin Sun, Liang Chen 0001, sheng Tian, Liang Zhu, Changhua Meng, Zibin Zheng, Weiqiang Wang. kdd 2023: 1268-1279 [doi]
- How Mask Matters: Towards Theoretical Understandings of Masked AutoencodersQi Zhang, Yifei Wang, Yisen Wang. nips 2022: [doi]
- VideoMAE V2: Scaling Video Masked Autoencoders with Dual MaskingLimin Wang, Bingkun Huang, Zhiyu Zhao, Zhan Tong, Yinan He, Yi Wang, Yali Wang, Yu Qiao. cvpr 2023: 14549-14560 [doi]
- Masking Improves Contrastive Self-Supervised Learning for ConvNets, and Saliency Tells You WhereZhi-Yi Chin, Chieh-Ming Jiang, Ching-Chun Huang, Pin-Yu Chen, Wei-chen Chiu. wacv 2024: 2749-2758 [doi]