| Graph based anomaly detection and description: a survey L Akoglu, H Tong, D Koutra Data mining and knowledge discovery 29, 626-688, 2015 | 1768 | 2015 |
| Beyond homophily in graph neural networks: Current limitations and effective designs J Zhu, Y Yan, L Zhao, M Heimann, L Akoglu, D Koutra Advances in neural information processing systems 33, 7793-7804, 2020 | 1030 | 2020 |
| Rolx: structural role extraction & mining in large graphs K Henderson, B Gallagher, T Eliassi-Rad, H Tong, S Basu, L Akoglu, ... Proceedings of the 18th ACM SIGKDD international conference on Knowledge …, 2012 | 573 | 2012 |
| Graph Summarization Methods and Applications: A Survey Y Liu, T Safavi, A Dighe, D Koutra ACM Computing Surveys (CSUR), 2018 | 461 | 2018 |
| Anomaly detection in dynamic networks: a survey S Ranshous, S Shen, D Koutra, S Harenberg, C Faloutsos, NF Samatova Wiley Interdisciplinary Reviews: Computational Statistics 7 (3), 223-247, 2015 | 455 | 2015 |
| Regal: Representation learning-based graph alignment M Heimann, H Shen, T Safavi, D Koutra Proceedings of the 27th ACM international conference on information and …, 2018 | 328 | 2018 |
| Graph neural networks with heterophily J Zhu, RA Rossi, A Rao, T Mai, N Lipka, NK Ahmed, D Koutra Proceedings of the AAAI conference on artificial intelligence 35 (12), 11168 …, 2021 | 326 | 2021 |
| DELTACON: A Principled Massive-Graph Similarity Function D Koutra, JT Vogelstein, C Faloutsos Proceedings of the 13th SIAM International Conference on Data Mining (SDM …, 2013 | 311 | 2013 |
| Two sides of the same coin: Heterophily and oversmoothing in graph convolutional neural networks Y Yan, M Hashemi, K Swersky, Y Yang, D Koutra 2022 IEEE International Conference on Data Mining (ICDM), 1287-1292, 2022 | 310 | 2022 |
| VOG: Summarizing and Understanding Large Graphs D Koutra, U Kang, J Vreeken, C Faloutsos SDM, 2014 | 270* | 2014 |
| BIG-ALIGN: Fast Bipartite Graph Alignment D Koutra, H Tong, D Lubensky IEEE ICDM, 2013 | 195 | 2013 |
| Timecrunch: Interpretable dynamic graph summarization N Shah, D Koutra, T Zou, B Gallagher, C Faloutsos Proceedings of the 21th ACM SIGKDD international conference on knowledge …, 2015 | 186 | 2015 |
| Detecting insider threats in a real corporate database of computer usage activity TE Senator, HG Goldberg, A Memory, WT Young, B Rees, R Pierce, ... Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013 | 180 | 2013 |
| DeltaCon Principled Massive-Graph Similarity Function with Attribution D Koutra, N Shah, JT Vogelstein, B Gallagher, C Faloutsos ACM Transactions on Knowledge Discovery from Data (TKDD) 10 (3), 1-43, 2016 | 170 | 2016 |
| Unifying guilt-by-association approaches: Theorems and fast algorithms D Koutra, TY Ke, U Kang, DH Chau, HKK Pao, C Faloutsos Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011 | 168 | 2011 |
| Algorithms for graph similarity and subgraph matching D Koutra, A Parikh, A Ramdas, J Xiang Proc. Ecol. inference conf 17, 2011 | 166 | 2011 |
| Netsimile: A scalable approach to size-independent network similarity M Berlingerio, D Koutra, T Eliassi-Rad, C Faloutsos arXiv preprint arXiv:1209.2684, 2012 | 155 | 2012 |
| Com2: fast automatic discovery of temporal (‘comet’) communities M Araujo, S Papadimitriou, S Günnemann, C Faloutsos, P Basu, A Swami, ... Advances in Knowledge Discovery and Data Mining: 18th Pacific-Asia …, 2014 | 137 | 2014 |
| On proximity and structural role-based embeddings in networks: Misconceptions, techniques, and applications RA Rossi, D Jin, S Kim, NK Ahmed, D Koutra, JB Lee ACM Transactions on Knowledge Discovery from Data (TKDD) 14 (5), 1-37, 2020 | 124* | 2020 |
| Codex: A comprehensive knowledge graph completion benchmark T Safavi, D Koutra arXiv preprint arXiv:2009.07810, 2020 | 119 | 2020 |
Christos FaloutsosCMU在 cs.cmu.edu 的电子邮件经过验证
