| The" majority illusion" in social networks K Lerman, X Yan, XZ Wu PloS one 11 (2), e0147617, 2016 | 143 | 2016 |
| Model selection for degree-corrected block models X Yan, C Shalizi, JE Jensen, F Krzakala, C Moore, L Zdeborová, P Zhang, ... Journal of Statistical Mechanics: Theory and Experiment 2014 (5), P05007, 2014 | 86 | 2014 |
| Scalable text and link analysis with mixed-topic link models Y Zhu, X Yan, L Getoor, C Moore Proceedings of the 19th ACM SIGKDD international conference on Knowledge …, 2013 | 53 | 2013 |
| Active learning for node classification in assortative and disassortative networks C Moore, X Yan, Y Zhu, JB Rouquier, T Lane Proceedings of the 17th ACM SIGKDD international conference on Knowledge …, 2011 | 46 | 2011 |
| The interplay between dynamics and networks: centrality, communities, and cheeger inequality R Ghosh, S Teng, K Lerman, X Yan Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 38 | 2014 |
| Oriented and degree-generated block models: generating and inferring communities with inhomogeneous degree distributions Y Zhu, X Yan, C Moore Journal of Complex Networks 2 (1), 1-18, 2014 | 30 | 2014 |
| Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining B Perozzi, R Al-Rfou, S Skiena ACM Press, 2014 | 28 | 2014 |
| A spectrum of routing strategies for brain networks A Avena-Koenigsberger, X Yan, A Kolchinsky, M van den Heuvel, ... PLoS computational biology 15 (3), e1006833, 2019 | 27 | 2019 |
| Weighted stochastic block models of the human connectome across the life span J Faskowitz, X Yan, XN Zuo, O Sporns Scientific reports 8 (1), 1-16, 2018 | 23 | 2018 |
| Bayesian model selection of stochastic block models X Yan 2016 IEEE/ACM International Conference on Advances in Social Networks …, 2016 | 17 | 2016 |
| Weight thresholding on complex networks X Yan, LGS Jeub, A Flammini, F Radicchi, S Fortunato Physical Review E 98 (4), 042304, 2018 | 14 | 2018 |
| Structural properties of ego networks S Gupta, X Yan, K Lerman International Conference on Social Computing, Behavioral-Cultural Modeling …, 2015 | 13 | 2015 |
| Modified Cheeger and ratio cut methods using the Ginzburg–Landau functional for classification of high-dimensional data E Merkurjev, A Bertozzi, X Yan, K Lerman Inverse Problems 33 (7), 074003, 2017 | 11 | 2017 |
| Graph Filters and the Z-Laplacian X Yan, BM Sadler, RJ Drost, LY Paul, K Lerman IEEE Journal of Selected Topics in Signal Processing 11 (6), 774-784, 2017 | 9 | 2017 |
| Information-theoretic clustering of neuroimaging metrics related to cognitive decline in the elderly M Daianu, G Ver Steeg, A Mezher, N Jahanshad, TM Nir, X Yan, G Prasad, ... International MICCAI Workshop on Medical Computer Vision, 13-23, 2015 | 8 | 2015 |
| Capturing the interplay of dynamics and networks through parameterizations of Laplacian operators X Yan, S Teng, K Lerman, R Ghosh PeerJ Computer Science 2, e57, 2016 | 6 | 2016 |
| Y. Zhu Model selection for degree-corrected block models X Yan, C Shalizi, JE Jensen, F Krzakala, C Moore, L Zdeborová, P Zhang J. Stat. Mech. P 5007, 2014 | 6 | 2014 |
| Active learning for hidden attributes in networks X Yan, Y Zhu, JB Rouquier, C Moore arXiv preprint arXiv:1005.0794, 2010 | 4 | 2010 |
| TBI2Flow: Travel behavioral inertia based long-term taxi passenger flow prediction X Kong, F Xia, Z Fu, X Yan, A Tolba, Z Almakhadmeh World Wide Web 23 (2), 1381-1405, 2020 | 3 | 2020 |
| The impact of air transport availability on research collaboration: A case study of four universities A Ploszaj, X Yan, K Borner arXiv preprint arXiv:1811.02106, 2018 | 2 | 2018 |
Kristina LermanPrincipal Scientist, USC Information Sciences Institute確認したメール アドレス: isi.edu
