Publications


The research presented here was partly supported by the National Science Foundation grants and a grant from NSA.


  • Huang, W., Liu, Y., and Chen, Y. (2019). Mixed Membership Stochastic Blockmodels for Heterogeneous Networks. Bayesian Analysis. In press.
  • Paul, S. and Chen, Y. (2019). Spectral and Matrix Factorization Methods for Consistent Community Detection in Multi-Layer Networks. The Annals of Statistics. In press.
  • Fredrickson, M. M. and Chen, Y. (2019). Permutation and Randomization Tests for Network Analysis. Social Networks. In press.
  • Zhang, J. and Chen, Y. (2019). Modularity Based Community Detection in Heterogeneous Networks. Statistica Sinica. In press.
  • Zimmerman B., Finnegan M., Paul S., Schmidt S., Tai Y., Roth K., Chen Y. and Husain F. T. (2019). Functional Brain Changes During Mindfulness-Based Cognitive Therapy Associated With Tinnitus Severity. Frontiers in Neuroscience, 13:747.
  • Chen, Y. and Chen, Y. (2018). An Efficient Sampling Algorithm for Network Motif Detection. Journal of Computational and Graphical Statistics, 27, 503-515.
  • Sengupta, S. and Chen, Y. (2018). A Block Model for Node Popularity in Networks with Community Structure. Journal of the Royal Statistical Society, Series B, 80, 365-386.
  • Eisinger, R. D. and Chen, Y. (2018). Sampling Strategies for Conditional Inference on Multigraphs. Statistics and Its Interface, 11, 649-656.
  • Huang, W., Shen, J., and Chen, Y. (2018). The Self-Multiset Sampler. Journal of Computational and Graphical Statistics, 27, 34-47
  • Chen, Y., Culpepper, S. A., Chen, Y., and Douglas, J. (2018). Bayesian Estimation of the DINA Q Matrix. Psychometrika, 83, 89-108.
  • Sewell, D. K. and Chen, Y. (2017). Latent Space Approaches to Community Detection in Dynamic Networks. Bayesian Analysis, 12, 351-377.
  • Zhang, J. and Chen, Y. (2017). A Hypothesis Testing Framework for Modularity Based Network Community Detection. Statistica Sinica, 27, 437-456.
  • Yun, J., Yang, F., and Chen, Y. (2017). Augmented Particle Filters. Journal of the American Statistical Association, 112, 300-313.
  • Eisinger, R. D. and Chen, Y. (2017). Sampling for Conditional Inference on Contingency Tables. Journal of Computational and Graphical Statistics, 26, 79-87.
  • Guidotti, R., Gardoni, P., and Chen, Y. (2017). Multi-Layer Heterogeneous Network Model for Interdependent Infrastructure Systems. Proceedings of the 12th International Conference on Structural Safety and Reliability, 2947-2956.
  • Huang, W. and Chen, Y. (2017). The Multiset EM Algorithm. Statistics and Probability Letters, 126, 41-48.
  • Guidotti, R., Gardoni, P., and Chen, Y. (2017). Network Reliability Analysis with Link and Nodal Weights and Auxiliary Nodes. Structural Safety, 65, 12-26.
  • Paul, S. and Chen, Y. (2016). Consistent Community Detection in Multi-Relational Data Through Restricted Multi-Layer Stochastic Blockmodel. Electronic Journal of Statistics, 10, 3807-3870.
  • Sewell, D. K., Chen, Y., Bernhard, W., and Sulkin, T. (2016). Model-Based Longitudinal Clustering with Varying Cluster Assignments. Statistica Sinica, 26, 205-233.
  • Sewell, D. K. and Chen, Y. (2016). Latent Space Models for Dynamic Networks with Weighted Edges. Social Networks, 44, 105-116.
  • Sewell, D. K. and Chen, Y. (2015). Latent Space Models for Dynamic Networks. Journal of the American Statistical Association, 110, 1646-1657.
  • Zhang, J. and Chen, Y. (2015). Monte Carlo Algorithms for Identifying Densely Connected Subgraphs. Journal of Computational and Graphical Statistics, 24, 827-845.
  • Sengupta, S. and Chen, Y. (2015). Spectral Clustering in Heterogeneous Networks. Statistica Sinica, 25, 1081-1106.
  • Sewell, D. K. and Chen, Y. (2015). Analysis of the Formation of the Structure of Social Networks using Latent Space Models for Ranked Dynamic Networks. Journal of the Royal Statistical Society, Series C, 64, 611-633.
  • Feng, Y., Chen, Y., and He, X. (2015). Bayesian Quantile Regression with Approximate Likelihood. Bernoulli, 21, 832-850.
  • Zhang, J. and Chen, Y. (2015). Exponential Random Graph Models for Networks Resilient to Targeted Attacks. Statistics and Its Interface, 8, 267-276.
  • Cheon, S., Liang, F., Chen, Y., and Yu, K. (2014). Stochastic Approximation Monte Carlo Importance Sampling for Approximating Exact Conditional Probabilities. Statistics and Computing, 24, 505-520.
  • Feng, X., Feng, Y., Chen, Y., and Small, D. S. (2014). Randomization Inference for the Trimmed Mean of Effects Attributable to Treatment. Statistica Sinica, 24, 773-797.
  • Zhang, J. and Chen, Y. (2013). Sampling for Conditional Inference on Network Data. Journal of the American Statistical Association , 108, 1295-1307.
  • Cui, N., Chen, Y., and Small, D. S. (2013). Modeling Parasite Infection Dynamics When There Is Heterogeneity and Imperfect Detectability. Biometrics, 69, 683–692.
  • Wang, C., Wang, H., Liu, J., Ji, M., Su, L., Chen, Y., and Han, J. (2013). On the Detectability of Node Grouping in Networks. Proceedings of the Thirteenth SIAM International Conference on Data Mining, 713-721.
  • Chen, Y. (2012). A Theory for the Multiset Sampler . Statistics and Probability Letters, 82, 473–477.
  • Wu, B., Lai, T. L., and Chen, Y. (2012). Sequential Planning for Robotic Navigation and Exploration under Uncertainty. In Introduction to Modern Robotics II, 47-68. iConcept Press.
  • Dinwoodie, I. H. and Chen, Y. (2011). Sampling Large Tables with Constraints . Statistica Sinica, 21, 1591-1609.
  • Yun, J. and Chen, Y. (2010). Discussion on “Particle Markov Chain Monte Carlo Methods” by C. Andrieu, A. Doucet, and R. Holstein. Journal of the Royal Statistical Society, Series B, 72, 332-333.
  • Wu, T., Chen, Y., and Han, J. (2010). Re-Examination of Interestingness Measures in Pattern Mining: A Unified Framework. Data Mining and Knowledge Discovery, 21, 371-397.
  • Leman, S. C., Chen, Y., and Lavine, M. (2009). The Multiset Sampler . Journal of the American Statistical Association . 104, 1029-1041.
  • Butala, M. D., Frazin, R. A., Chen, Y., and Kamalabadi, F. (2009). Tomographic Imaging of Dynamic Objects With the Ensemble Kalman Filter. IEEE Transactions on Image Processing, 18, 1573-1587.
  • Chen, Y., Dinwoodie, I. H., and Yoshida, R. (2009). Markov Chains, Quotient Ideals, and Connectivity with Positive Margins. In Algebraic and Geometric Methods in Statistics, 99-110. Cambridge University Press.
  • Wang, D., Chen, Y., and Cai, X. (2009). State and Parameter Estimation of Hydrologic Models Using the Constrained Ensemble Kalman Filter. Water Resources Research, 45, W11416, doi:10.1029/2008WR007401.
  • Xie, H., Eheart, J.W., Chen, Y., and Bailey, B.A. (2009). An Approach for Improving the Sampling Efficiency in the Bayesian Calibration of Computationally Expensive Simulation Models. Water Resources Research, 45, W06419, doi:10.1029/2007WR006773.
  • Li, S., Hartman, G. L., and Chen, Y. (2009). Evaluation of Aggressiveness of Fusarium Virguliforme Isolates That Cause Soybean Sudden Death Syndrome. Journal of Plant Pathology, 91, 77-86.
  • Chen, Y., Lai, T. L., and Wu, B. (2009). Fast Particle Filters and Their Applications to Adaptive Control in Change-Point ARX Models and Robotics. In Frontiers in Adaptive Control, 51-70. In-Tech, Vienna, Austria.
  • Chen, Y. (2009). Sequential Importance Sampling with Resampling in Molecular Population Genetics. In Frontiers of Biostatistics and Bioinformatics, 16-39. University of Science and Technology of China Press.
  • Butala, M. D., Kamalabadi, F., Frazin, R. A., and Chen, Y. (2008). Dynamic Tomographic Imaging of the Solar Corona. IEEE Journal of Selected Topics in Signal Processing, 2, 755-766.
  • Butala, M. D., Yun, J., Chen, Y., Frazin, R. A., and Kamalabadi, F. (2008). Asymptotic Convergence of the Ensemble Kalman Filter. Proceedings of the 2008 IEEE International Conference on Image Processing, 825-828.
  • Xie, J., Yang, J., Chen, Y., Wang, H., and Yu. P. S. (2008). A Sampling-Based Approach to Information Recovery. Proceedings of the 24th International Conference on Data Engineering, 476-485.
  • Chen, Y., Dinwoodie, I. H., and MacGibbon, B. (2007). Sampling for Conditional Inference on Case-Control Data. Biometrics, 63, 845-855.
  • Leman, S. C., Uyenoyama, M. K., Lavine, M., and Chen, Y. (2007). The Evolutionary Forest Algorithm. Bioinformatics, 23, 1962-1968.
  • Wu, T, Chen, Y., and Han, J. (2007). Association Mining in Large Databases: A Re-Examination of Its Measures. Proceedings of the 11th European Conference on Principles and Practice of Knowledge Discovery in Databases, 621-628.
  • Chen, Y. and Liu, J. S. (2007). Sequential Monte Carlo Methods for Permutation Tests on Truncated Data. Statistica Sinica, 17, 857-872.
  • Chen, Y. (2007). Conditional Inference on Tables with Structural Zeros. Journal of Computational and Graphical Statistics, 16, 445-467. Software associated with this paper.
  • Butala, M. D., Frazin, R. A., Chen, Y., and Kamalabadi, F. (2007). A Monte Carlo Technique for Large-Scale Dynamic Tomography. Proceedings of the 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing, Vol. 3, III-1217-III-1220.
  • Chen, Y. and Lai, T. L. (2007). Identification and Adaptive Control of Change-Point ARX Models via Rao-Blackwellized Particle Filters. IEEE Transactions on Automatic Control, 52, 67-72
  • Chen, Y., Lin, C. H., and Sabatti, C. (2006). Volume Measures for Linkage Disequilibrium. BMC Genetics, 7:54. Software associated with this paper.
  • Wang, H., Lin, C. H., Service, S., Chen, Y., Freimer, N., Sabatti, C., and The international collaborative group on isolated populations (2006). Linkage Disequilibrium and Haplotype Homozygosity in Population Samples Genotyped at a High Marker Density. Human Heredity, 62, 175-189.
  • Chen, Y. (2006). Simple Existence Conditions for Zero-One Matrices with at Most One Structural Zero in Each Row and Column. Discrete Mathematics, 306, 2870-2877.
  • Chen, Y., Dinwoodie, I. H., and Sullivant, S. (2006). Sequential Importance Sampling for Multiway Tables. The Annals of Statistics , 34, 523-545.
  • Huber, M., Chen, Y., Dinwoodie, I., Dobra, A. and Nicholas, M. (2006). Monte Carlo Algorithms for Hardy-Weinberg Proportions. Biometrics, 62, 49-53.
  • Leman, S. C., Chen, Y., Stajich, J. E., Noor, M. A. F., and Uyenoyama, M. K. (2005). Likelihoods from Summary Statistics: Recent Divergence Between Species. Genetics, 171, 1419-1436.
  • Chen, Y. and Small, D. (2005). Exact Tests for the Rasch Model via Sequential Importance Sampling. Psychometrika, 70, 11-30.
  • Chen, Y. (2005). Another Look at Rejection Sampling Through Importance Sampling. Statistics and Probability Letters, 72, 277-283.
  • Chen, Y., Diaconis, P., Holmes, S. and Liu, J.S. (2005). Sequential Monte Carlo Methods for Statistical Analysis of Tables. Journal of the American Statistical Association, 100, 109-120.
  • Chen, Y., Xie, J., and Liu, J.S. (2005). Stopping-Time Resampling for Sequential Monte Carlo Methods. Journal of the Royal Statistical Society, Series B, 67, 199-217.
  • Chen, Y., Dinwoodie, I., Dobra, A. and Huber, M. (2005). Lattice Points, Contingency Tables, and Sampling. In Contemporary Mathematics, Vol. 374, 65-78. American Mathematical Society.
  • Xie, J., Yang, J. and Chen, Y. (2005). On Joining and Caching Stochastic Streams. Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data, 359-370.
  • Yi, K., Yu, H., Yang, J., Xia, G. and Chen, Y. (2003). Efficient Maintenance of Materialized Top-k Views. Proceedings of the 19th International Conference on Data Engineering, 189-200.
  • Chen, Y. and Lai, T. L. (2003). Sequential Monte Carlo Methods for Filtering and Smoothing in Hidden Markov Models. Technical Report 2003-18, Department of Statistics, Stanford University.
  • Chen, Y. and Liu, J.S. (2000). Discussion on “Inference in Molecular
    Population Genetics” by M. Stephens and P. Donnelly. Journal of the Royal Statistical Society, Series B, 62, 644-645.