3 citations · 11 across the 4 of their papers we have counts for
4 papers
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…
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…
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…
Co-supervised learning paradigm with conditional generative adversarial networks for sample-efficient classification
Hao Zhen, Yucheng Shi, Jidong J. Yang +1
Classification using supervised learning requires annotating a large amount of classes-balanced data for model training and testing. This has practically limited the scope of appli…