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An Efficient Procedure for Mining Egocentric Temporal Motifs., , , and . CoRR, (2021)Global Explainability of GNNs via Logic Combination of Learned Concepts., , , , and . ICLR, OpenReview.net, (2023)A Simple Latent Variable Model for Graph Learning and Inference., , , , and . LoG, volume 231 of Proceedings of Machine Learning Research, page 26. PMLR, (2023)A Unified Active Learning Framework for Annotating Graph Data with Application to Software Source Code Performance Prediction., , , , and . CoRR, (2023)Putting Context in Context: the Impact of Discussion Structure on Text Classification., , , , and . EACL (1), page 1793-1811. Association for Computational Linguistics, (2024)TEP-GNN: Accurate Execution Time Prediction of Functional Tests Using Graph Neural Networks., , , , and . PROFES, volume 13709 of Lecture Notes in Computer Science, page 464-479. Springer, (2022)Explaining the Explainers in Graph Neural Networks: a Comparative Study., , , , , , and . CoRR, (2022)Global Explainability of GNNs via Logic Combination of Learned Concepts., , , , and . CoRR, (2022)Patterns in Temporal Networks with Higher-Order Egocentric Structures., , , , and . Entropy, 26 (3): 256 (March 2024)An efficient procedure for mining egocentric temporal motifs., , , and . Data Min. Knowl. Discov., 36 (1): 355-378 (2022)