Publications

19. Yan, X., Sporns, O., and Avena-Koenigsberger, A. (2020). Efficient network navigation with partial information. To appear in the Proceedings of the 2020 IEEE International Conference on Networking, Sensing and Control (ICNSC2020)
18. Kong, X., Xia, F., Fu, Z., Yan, X., Tolba, A., and Almakhadmeh, Z. (2019). TBI2Flow: Travel behavioral inertia based long-term taxi passenger flow prediction. World Wide Web Journal. Special Issue on Smart Computing and Cyber Technology for Cyberization

17. Ploszaj, A., Yan, X., and Borner, K. (2019). The impact of air transport availability on research collaboration. In Proceedings of the ISSI 2019 Conference

16. Avena-Koenigsberger, A., Yan, X., Kolchinsky, A., Van den Heuvel, M., Hagmann, P., and Sporns, O. (2019). A spectrum of routing strategies for brain networks. PLOS Computational Biology. 15(3), pp.e1006833-e1006833
15. Yan, X., Jeub, L., Flammini, A., Radicchi, F., and Fortunato, S. Weight Thresholding on Complex Networks. Accepted by Physical Review E, Issue/Batch: 10_05_18 (2018) https://arxiv.org/abs/1806.07479
14. Faskowitz, J., Yan, X., Zuo, X.-N., and Sporns, O. (2018) Weighted Stochastic Block Models of the Human Connectome across the Life Span. Scientific reports, 8(1):12997. https://www.nature.com/articles/s41598-018-31202-1
13. Yan, X., Sadler, B. M., Drost, R. J., Yu, P. L. & Lerman, K. Graph Filters and the
Z-Laplacian. IEEE Journal of Selected Topics in Signal Processing 11, 774–784 (2017).http://ieeexplore.ieee.org/document/7986982/
12. Yan, X., Teng, S.-H. & Lerman, K. Multi-layer Network Composition Under a Unified
Dynamical Process. in Social, Cultural, and Behavioral Modeling: 10th International Conference, SBP-BRiMS 2017, Washington, DC, USA, July 5-8, 2017, Proceedings 315–321 (Springer International Publishing, 2017). doi:10.1007/978-3-319-60240-0_38
11.
Merkurjev, E., Bertozzi, A., Yan, X. & Lerman, K. Modified Cheeger and ratio cut methods using the Ginzburg–Landau functional for classification of high-dimensional data. Inverse Problems 33, 074003 (2017).
10.
Yan, X. Bayesian Model Selection for Stochastic Block Models. In 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pages 323–328 https://arxiv.org/abs/1605.07057
9.
Yan,X., Teng S., Lerman K., Ghosh R. Capturing the interplay of dynamics and  networks through parameterizations of Laplacian operators. https://peerj.com/articles/cs-57/
8.
Lerman, K., Yan, X. & Wu, X.-Z. The Majority Illusion in Social Networks. PLoS One (2016). http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0147617
7.
Daianu, M. et al. Information-theoretic Characterization of Neuroimaging Derived Metrics for Cognitive Decline in the Elderly. (2015).
6.
Gupta, S., Yan, X. & Lerman, K. Structural Properties of Ego Networks. in Social Computing, Behavioral-Cultural Modeling, and Prediction (eds. Agarwal, N., Xu, K. & Osgood, N.) 9021, 55–64 (Springer International Publishing, 2015). https://arxiv.org/pdf/1411.6061.pdf
5.
Ghosh, R., Teng, S., Lerman, K. & Yan, X. The Interplay Between Dynamics and Networks: Centrality, Communities, and Cheeger Inequality. in Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 1406–1415 (ACM, 2014). http://doi.acm.org/10.1145/2623330.2623738

Source code: https://github.com/everyxs/SBMbp/releases

4.
Zhu, Y., Yan, X. & Moore, C. Oriented and degree-generated block models: generating and inferring communities with inhomogeneous degree distributions. Journal of Complex Networks2, 1–18 (2014). http://comnet.oxfordjournals.org/content/2/1/1.abstract
3.
Yan, X. et al. Model selection for degree-corrected block models. Journal of Statistical Mechanics: Theory and Experiment2014, P05007 (2014). http://stacks.iop.org/1742-5468/2014/i=5/a=P05007
Source code: https://github.com/everyxs/gephi-plugins/releases
2.
Zhu, Y., Yan, X., Getoor, L. & Moore, C. Scalable Text and Link Analysis with Mixed-topic Link Models. in Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 473–481 (ACM, 2013). http://doi.acm.org/10.1145/2487575.2487693
1.
Moore, C., Yan, X., Zhu, Y., Rouquier, J.-B. & Lane, T. Active Learning for Node Classification in Assortative and Disassortative Networks. in Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 841–849 (ACM, 2011). http://doi.acm.org/10.1145/2020408.2020552
Source code: https://github.com/everyxs/gephi-plugins/releases