36 citations · 115 across the 10 of their papers we have counts for
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cs.LG2021★ 36 cited
Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration
Xiao Wang, Hongrui Liu, Chuan Shi +1
Despite Graph Neural Networks (GNNs) have achieved remarkable accuracy, whether the results are trustworthy is still unexplored. Previous studies suggest that many modern neural ne…
cs.CY2021★ 1 cited
From Symbols to Embeddings: A Tale of Two Representations in Computational Social Science
Huimin Chen, Cheng Yang, Xuanming Zhang +3
Computational Social Science (CSS), aiming at utilizing computational methods to address social science problems, is a recent emerging and fast-developing field. The study of CSS i…
cs.LG2021★ 3 cited
Evaluating Modules in Graph Contrastive Learning
Ganqu Cui, Yufeng Du, Cheng Yang +5
The recent emergence of contrastive learning approaches facilitates the application on graph representation learning (GRL), introducing graph contrastive learning (GCL) into the li…