Refereed Papers

Most of these are available on arXiv. Corresponding software is available at the bottom of this page.

For a broad description of current interests, see my research page.

Preprints

(* denotes equal contribution)

Suder, P., Xu, J and Dunson, D. Bayesian Transfer Learning. Minor revision. Link
Morsomme, R. and Xu, J. Exact Inference for Stochastic Epidemic Models via Uniformly Ergodic Block Sampling. Minor revision (ASA Statistics in Epidemiology Young Investigator Paper Award). Link
Morsomme, R., Halloway, S., Ryser, M.* and Xu, J*. A Bayesian approach for fitting semi-Markov mixture models of cancer latency to individual-level screens.
Zheng, C., Dilma, E., Xu, J. and Duan, L. The Bridged Posterior: Optimization, Profile Likelihood and a New Approach to Generalized Bayes. Link
Morsomme, R.*, Chen, M.*, and Xu, J. A family of flexible and scalable temporal stochastic epidemic models.
He, M., Lu, D., Xu, J.* and Xavier, R*. Community Detection in Weighted Multilayer Networks with Ambient Noise. Link
Gustafson, A., Hirn, M., Mohammed, K., Narayanan, H. and Xu, J. Structural Risk Minimization for C^1,1(R^d) Regression. Link

Thesis

Xu, J. (2016). Likelihood-Based Inference for Partially Observed Multi-Type Markov Branching Processes. PhD Dissertation, Department of Statistics, University of Washington. Link

Publications

(* denotes equal contribution)

Chandra, N., Dunson, D. and Xu, J. (2024). Inferring Covariance Structure from Multiple Data Sources via Subspace Factor Analysis. Journal of the American Statistical Association. Link
Jiang, H. and Xu, J. The Stochastic Proximal Distance Algorithm. (ASA Statistical Computing and Statistical Graphics Section Student Paper Competition Award). Statistics and Computing. Link
Bu, F., Aiello, A., Volfovsky, A.* and Xu, J.* (2024). Stochastic EM algorithm for partially observed stochastic epidemics with individual heterogeneity. Biostatistics. Link
Agarwal, M. and Xu, J. (2024). Quasi-Newton Acceleration of EM and MM Algorithms via Broyden’s Method with Extrapolation. Journal of Computational and Graphical Statistics. Link
Huang, J., Morsomme, R., Dunson, D. and Xu, J. (2024). Detecting Changes in the Transmission Rate of a Stochastic Epidemic Model. Statistics in Medicine. Link
Bu, F., Galiwango, R., Grabowski, K., Ratmann, O. and Xu, J. (2024). Inferring HIV Transmission Patterns from Viral Deep-Sequence Data via Latent Typed Point Processes. Biometrics. Link
Awasthi, A., Minin, V., Huang, J., Chow, D. and Xu, J. (2023). Fitting a Stochastic Model of Intensive Care Occupancy to Noisy Hospitalization Time Series. Statistics in Medicine. Link
Landeros, A., Xu, J. and Lange, K. (2023). MM Optimization Algorithms: Proximal Distance Algorithms, Path Following, and Trust Regions. Proceedings of the National Academy of Sciences (PNAS). Link
Presman, R. and Xu, J. (2023). Distance-to-Set Priors and Constrained Bayesian Inference. Artificial Intelligence and Statistics. (Oral) Link
Awasthi, A. and Xu, J. (2023). Fast Computation of Branching Process Transition Probabilities via ADMM. Artificial Intelligence and Statistics. Link
Won, J., Lange, K. and Xu, J. (2023). A Unified Analysis of Convex and Non-convex l_p-ball Projection Problems. Optimization Letters. Link
Paul, D.*, Chakraborty, S.*, Das, S. and Xu, J. (2023). Implicit Annealing in Kernel and Multi-kernel Spaces: A Strongly Consistent Clustering Approach. IEEE Transactions in Pattern Analysis and Machine Intelligence. Link
Chakraborty, S. and Xu, J. (2023). Biconvex Clustering. Journal of Computational and Graphical Statistics. Link
Xu, J. and Lange, K. (2022). A Proximal Distance Algorithm for Likelihood-based Sparse Covariance Estimation. Biometrika. Link
Scalabrino, M.L, Thapa , M., Chew, L. A., Zhang, E., Xu, J., Sampath, A. P., Chen, J., Field, G.D. (2022). Robust Cone-mediated Signaling Persists Late into Rod Photoreceptor Degeneration. eLife. Link
Vellal, A., Chakraborty, S. and Xu, J. (2022). Bregman Power k-Means for Clustering Exponential Family Data. International Conference on Machine Learning. Link
Bu, F., Aiello, A., Xu, J.* and Volfovsky, A* (2022). Likelihood-based Inference for Partially Observed Epidemics on Dynamic Networks. Journal of the American Statistical Association. (SBSS Student Paper Award) Link
Stutz, T., Sehl, M., Sinsheimer, J. and Xu, J (2022). Computational Tools for Assessing Gene Therapy under Branching Process Models of Mutation. Bulletin of Mathematical Biology. Link
Paul, D.*, Chakraborty, S.*, Das, S. and Xu, J (2021). Uniform Concentration Bounds toward a Unified Framework for Robust Clustering. Neural Information Processing Systems (NeurIPS). (Spotlight Paper) Link
Landeros, A., Ji, X., Lange, K. L., Stutz, T., Xu, J., Sehl, M. E.*, and Sinsheimer, J.S* (2021). An Examination of School Reopening Strategies during the SARS-CoV-2 Pandemic. PLOS One. Link
Ciccone, E.J., et al. (2021). SARS-CoV-2 Infection in Healthcare Personnel and Their Household Contacts at a Tertiary Academic Medical Center: Protocol for a Longitudinal Cohort Study. JMIR Research Protocols. Link
Stutz, T., Landeros, A., Xu, J., Sinsheimer, J. S., Lange, K. and Sehl, M. E (2021). Stochastic Simulation Algorithms for Interacting Particle Systems. PLOS One. Link
Zhang, Z., Lange, K. and Xu, J. (2020). Simple and Scalable Sparse k-Means Clustering via Feature Ranking. Neural Information Processing Systems (NeurIPS). (Spotlight Paper) Link
Chakraborty, S.*, Paul, D.*, Das, S. and Xu, J. (2020). Entropy Weighted Power k-Means Clustering. Artificial Intelligence and Statistics (AISTATS). Link
Xu, J., Koelle, S., Wu, C., Guttorp, P., Dunbar, C. E., Abkowitz, J. L. and Minin, V. N. (2019). Statistical Inference for Partially Observed Branching Processes, with Application to Cell Lineage Tracking of in vivo Hematopoiesis. The Annals of Applied Statistics. Link
Xu, J. and Lange, K (2019). Power k-Means Clustering. International Conference on Machine Learning (ICML). (Long Oral) Link
Won, J., Xu, J and Lange, K. (2019). Projection onto Minkowski Sums with Application to Constrained Learning. International Conference on Machine Learning (ICML). (Long Oral) Link
Xu, J., Wang, Y., Guttorp, P. and Abkowitz, J. L. (2018). Visualizing Hematopoiesis as a Stochastic Process. Blood. Link
Ho, L., Xu, J., Crawford, F. W., Minin, V. N. and Suchard, M. A. (2018). Birth/birth-death Processes and their Computable Transition Probabilities with Biological Applications. Journal of Mathematical Biology. Link
Xu, J., Chi, E., Yang, M. and Lange, K. (2018). A Majorization-minimization Algorithm for Split Feasibility Problems. Computational Optimization and Applications. Link
Xu, J., Chi, E. and Lange, K. (2018). Generalized Linear Model Regression under Distance-to-set Penalties. Neural Information Processing Systems (NeurIPS). (Spotlight Paper) Link
Letcher, A.*, Trišović, J.*, Cademartori, C., Chen, X. and Xu, J. (2018). Automatic Conflict Detection in Police Body-Worn Audio. Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). (MAA Outstanding Student Research Award) Link
Hardin, W., Li, R., Xu, J., Shelton, A., Alas G., Minin, V. N. and Paredez, A. R. (2017). Myosin-independent cytokinesis in Giardia Utilizes Flagella to Coordinate Force Generation and Direct Membrane Trafficking. Proceedings of the National Academy of Sciences (PNAS). Link
Koelle, S., Wu, C., Xu, J., Lu, R., Li, B., Donahue, R. E. and Dunbar, C. E. (2017). Quantitative Stability of Hematopoietic Stem and Progenitor Cell Clonal Output in Rhesus Macaques Receiving Transplants. Blood. Link
Xu, J., Koelle, S., Wu, C., Guttorp, P., Dunbar, C. E., Abkowitz, J. L. and Minin, V. N. (2016). Stochastic Modeling of Hematopoietic Stem and Progenitor Cell Barcoding Data from Rhesus Macaques Challenges the Classic Model of Hematopoiesis. Blood. Link
Xu, J., Guttorp, P., Kato-Maeda, M. and Minin, V. N. (2015). Likelihood-based Inference for Discretely Observed Birth-death-shift Processes, with Applications to Evolution of Mobile Genetic Elements. Biometrics. (David P. Byar Paper Competition Award) Link
Xu, J. and Minin, V. N. (2015). Efficient Transition Probability Computation for Continuous-time Branching Processes via Compressed Sensing. Uncertainty in Artificial Intelligence (UAI). Link
Foti, N.*, Xu, J.*, Laird, D. and Fox, E. B. (2015). Stochastic Variational Inference for Hidden Markov Models. Neural Information Processing Systems (NeurIPS). Link
Huber, M. L., McCall, E., Rozenfeld, D. and Xu, J. (2012). Bounds on the Artificial Phase Transition for Perfect Simulation of Repulsive Point Processes. Involve. Link

Software

SUFA: R package for identifiable subspace factor analysis, with fast parallelized HMC-within-Gibbs sampler
HIVflow: R and Python code for learning transmission flow in latent spatial point process model of transmission structure via data-augmented MCMC
BCC: R code, biconvex clustering with adaptive feature selection
PDSIR: R package, fast data-augmented MCMC for sampling from the exact stochastic SIR posterior under incidence data
- Extension with change-point detection and heterogeneous transmission rate here!
QNMM: R package for quasi-Newton acceleration of MM and EM algorithms
SKFR: R and Julia code for sparse k-means with feature ranking
spcov: Julia implementation of proximal distance algorithm for sparse covariance estimation
pkmeans: Python implementation of power k-means including Bregman divergences
CoEpiNet: R code for inference for partially observed epidemics over dynamic contact networks
EWP: R code for power k-means clustering with entropy-based feature weighing
MinkowskiProjection: Matlab code for projection onto Minkowski sums of sets
splitFeas: R package, MM algorithms for multi-set split feasibility problems
branchCorr: R package, M-estimation for partially observed stochastic compartmental models
bdsem: R package, MLE and EM inference for discretely observed multi-type branching processes
pysvihmm: Python implementation of stochastic variational inference for hidden Markov models
multiBD: R package, likelihood inference for partially observed multivariate birth-death processes
hematopoiesisSimulator: Java GUI for simulating and visualizing stochastic models of hematopoiesis

Please email me for any code not yet released in a completed package.

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