3 citations · 11 across the 4 of their papers we have counts for
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cs.LG2023★ 3 cited
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction
Yucheng Shi, Yushun Dong, Qiaoyu Tan +2
Self-supervised learning with masked autoencoders has recently gained popularity for its ability to produce effective image or textual representations, which can be applied to vari…
cs.LG2023★ 2 cited
ENGAGE: Explanation Guided Data Augmentation for Graph Representation Learning
Yucheng Shi, Kaixiong Zhou, Ninghao Liu
The recent contrastive learning methods, due to their effectiveness in representation learning, have been widely applied to modeling graph data. Random perturbation is widely used…
cs.LG2023★ 3 cited
Interpretation of Time-Series Deep Models: A Survey
Ziqi Zhao, Yucheng Shi, Shushan Wu +3
Deep learning models developed for time-series associated tasks have become more widely researched nowadays. However, due to the unintuitive nature of time-series data, the interpr…