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DEvIANT: Discovering Significant Exceptional (Dis-)Agreement Within Groups.

, , , , and . ECML/PKDD (1), volume 11906 of Lecture Notes in Computer Science, page 3-20. Springer, (2019)

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Mining Disjunctive Rules in Dynamic Graphs., , and . RIVF, page 1-6. IEEE, (2012)Improving the Quality of Rule-Based GNN Explanations., , , and . PKDD/ECML Workshops (1), volume 1752 of Communications in Computer and Information Science, page 467-482. Springer, (2022)Qu'est-ce que mon GNN capture vraiment ? Exploration des représentations internes d'un GNN., , , , and . EGC, volume E-38 of RNTI, page 159-170. Editions RNTI, (2022)Exceptional Attributed Subgraph Mining to Understand the Olfactory Percept., , , , and . DS, volume 11198 of Lecture Notes in Computer Science, page 276-291. Springer, (2018)Contrastive Antichains in Hierarchies., , , , and . KDD, page 294-304. ACM, (2019)Mining unexpected multidimensional rules., , , , and . DOLAP, page 89-96. ACM, (2007)HYPE: mining hierarchical sequential patterns., , and . DOLAP, page 19-26. ACM, (2006)Sequential Patterns to Discover and Characterise Biological Relations., , and . CICLing, volume 6008 of Lecture Notes in Computer Science, page 537-548. Springer, (2010)Extraction De Motifs Séquentiels Dans Des Données Multidimensionelles. (Mining Sequential Patterns In Multidimensional Data).. Montpellier 2 University, France, (2008)Mining Subjectively Interesting Attributed Subgraphs., , , , , and . CoRR, (2019)