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Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices.

, , , , and . WWW, page 1538-1549. ACM, (2022)

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TimeCrunch: Interpretable Dynamic Graph Summarization., , , , and . KDD, page 1055-1064. ACM, (2015)Fast anomaly detection despite the duplicates., , , and . WWW (Companion Volume), page 195-196. International World Wide Web Conferences Steering Committee / ACM, (2013)Toward Understanding and Evaluating Structural Node Embeddings., , , and . ACM Trans. Knowl. Discov. Data, 16 (3): 58:1-58:32 (2022)Bridging Network Embedding and Graph Summarization., , , , , and . CoRR, (2018)Size Generalizability of Graph Neural Networks on Biological Data: Insights and Practices from the Spectral Perspective., , and . CoRR, (2023)Distribution of Node Embeddings as Multiresolution Features for Graphs., , and . ICDM, page 289-298. IEEE, (2019)Augmentations in Graph Contrastive Learning: Current Methodological Flaws & Towards Better Practices., , , , and . WWW, page 1538-1549. ACM, (2022)Events and Controversies: Influences of a Shocking News Event on Information Seeking., , and . WWW, page 614-624. ACM, (2015)A Closer Look At Scoring Functions And Generalization Prediction., , and . ICASSP, page 1-5. IEEE, (2023)Smart Roles: Inferring Professional Roles in Email Networks., , , , , , and . KDD, page 2923-2933. ACM, (2019)