A fundamental challenge of bipartite graph representation learning is how to extract
informative node embeddings. Self-Supervised Learning (SSL) is a promising paradigm to …

Machine learning over graphs has recently attracted growing attention due to its ability to
analyze and learn complex relations within critical interconnected systems. However, the …

Anomaly detection on graphs plays an important role in many real-world applications.
Usually, these data are composed of multiple types (eg, user information and transaction …

Learning a fair and privacy-preserving graph neural network from private and limited
sensitive attributes Page 1 P osted on 1 Aug 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/tech …