3 citations · 7 across the 8 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.SI2023★ 1 cited
Learning Diffusions under Uncertainty
Hao Huang, Qian Yan, Keqi Han +4
To infer a diffusion network based on observations from historical diffusion processes, existing approaches assume that observation data contain exact occurrence time of each node…
cs.LG2023★ 2 cited
Generative and Contrastive Paradigms Are Complementary for Graph Self-Supervised Learning
Yuxiang Wang, Xiao Yan, Chuang Hu +5
For graph self-supervised learning (GSSL), masked autoencoder (MAE) follows the generative paradigm and learns to reconstruct masked graph edges or node features. Contrastive Learn…