| Advanced modularity-specialized label propagation algorithm for detecting communities in networks X Liu, T Murata Physica A: Statistical Mechanics and its Applications 389 (7), 1493-1500, 2010 | 301 | 2010 |
| Community detection in large-scale bipartite networks X Liu, T Murata Transactions of the Japanese Society for Artificial Intelligence 25 (1), 16-24, 2010 | 133 | 2010 |
| An unsupervised learning method with convolutional auto-encoder for vessel trajectory similarity computation M Liang, RW Liu, S Li, Z Xiao, X Liu, F Lu Ocean Engineering 225, 108803, 2021 | 101 | 2021 |
| Graph convolutional networks for graphs containing missing features H Taguchi, X Liu, T Murata Future Generation Computer Systems 117, 155-168, 2021 | 86 | 2021 |
| Effective algorithm for detecting community structure in complex networks based on GA and clustering X Liu, D Li, S Wang, Z Tao Computational Science–ICCS 2007, 657-664, 2007 | 81 | 2007 |
| Simplifying approach to node classification in graph neural networks SK Maurya, X Liu, T Murata Journal of Computational Science 62, 101695, 2022 | 79 | 2022 |
| A general view for network embedding as matrix factorization X Liu, T Murata, KS Kim, C Kotarasu, C Zhuang Proceedings of the Twelfth ACM international conference on web search and …, 2019 | 70 | 2019 |
| A framework for community detection in heterogeneous multi-relational networks X Liu, W Liu, T Murata, K Wakita Advances in Complex Systems 17 (06), 1450018, 2014 | 59 | 2014 |
| An efficient algorithm for optimizing bipartite modularity in bipartite networks X Liu, T Murata Journal of Advanced Computational Intelligence and Intelligent Informatics …, 2010 | 50 | 2010 |
| Learning community structure with variational autoencoder JJ Choong, X Liu, T Murata 2018 IEEE International Conference on Data Mining (ICDM), 69-78, 2018 | 47 | 2018 |
| Graph neural networks for fast node ranking approximation SK Maurya, X Liu, T Murata ACM Transactions on Knowledge Discovery from Data (TKDD) 15 (5), 1-32, 2021 | 43 | 2021 |
| How does label propagation algorithm work in bipartite networks? X Liu, T Murata 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and …, 2009 | 41 | 2009 |
| Improving graph neural networks with simple architecture design SK Maurya, X Liu, T Murata arXiv preprint arXiv:2105.07634, 2021 | 40 | 2021 |
| Population graph-based multi-model ensemble method for diagnosing autism spectrum disorder Z Rakhimberdina, X Liu, T Murata Sensors 20 (21), 6001, 2020 | 39 | 2020 |
| Forecasting ambulance demand with profiled human mobility via heterogeneous multi-graph neural networks Z Wang, T Xia, R Jiang, X Liu, KS Kim, X Song, R Shibasaki 2021 IEEE 37th International Conference on Data Engineering (ICDE), 1751-1762, 2021 | 38 | 2021 |
| Fast approximations of betweenness centrality with graph neural networks SK Maurya, X Liu, T Murata Proceedings of the 28th ACM international conference on information and …, 2019 | 38 | 2019 |
| Food sales prediction with meteorological data—a case study of a Japanese chain supermarket X Liu, R Ichise Data Mining and Big Data: Second International Conference, DMBD 2017 …, 2017 | 35 | 2017 |
| Detecting Communities in K-Partite K-Uniform (Hyper)Networks X Liu, T Murata Journal of Computer Science and Technology 26 (5), 778, 2011 | 33 | 2011 |
| Natural image reconstruction from fmri using deep learning: A survey Z Rakhimberdina, Q Jodelet, X Liu, T Murata Frontiers in neuroscience 15, 795488, 2021 | 32 | 2021 |
| Towards an aggregator that exploits big data to bid on frequency containment reserve market C Giovanelli, X Liu, S Sierla, V Vyatkin, R Ichise IECON 2017-43rd Annual Conference of the IEEE Industrial Electronics Society …, 2017 | 32 | 2017 |
