Research

Pipeline

  • A Correlated Pseudo-marginal Approach to Doubly Intractable Problems (with Yu Yang, Robert Kohn and Scott Sisson). ArXiv. 

Peer-reviewed Publications

  • Quiroz, M., Nott, D.J. and Kohn, R. (2023). Gaussian Variational Approximation for High-dimensional State Space Models. Bayesian Analysis, 18(3): 989-1016. ArXiv. 
  • Villani, M., Quiroz, M., Kohn, R. and Salomone, R. (2022). Spectral Subsampling MCMC for Stationary Multivariate Time Series with Applications to Vector ARTFIMA Processes. Econometrics and Statistics. To appear. ArXiv.
  • Quiroz, M., Tran, M-N., Villani, M., Kohn, R. and Dang, K-D. (2021). The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC. Journal of Computational and Graphical Statistics, 30 (4):877-888. ArXiv. Journal.
  • Gunawan, D., Dang, K-D., Quiroz, M., Kohn, R., Tran, M-N. (2020). Subsampling Sequential Monte Carlo for Static Bayesian Models. Statistics and Computing, 30:1741-1758. ArXiv. Journal.
  • Salomone, R., Quiroz, M., Kohn, R., Villani, M. and Tran, M-N. (2020). Spectral Subsampling MCMC for Stationary Time Series. In Proceedings of International Conference on Machine Learning (ICML), pp. 10510-10519. ArXiv. Proceedings.
  • Adams, M. P., Koh, E. J. Y., Vilas, M. P., Collier. C. J., Lambert, V. M., Sisson, S. A.,  Quiroz, M., McDonald-Madden, E., McKenzie, L. J. and O’Brien K. R. (2020). Predicting Seagrass Decline due to Cumulative Stressors. Environmental Modelling and Software, 130:104717. Journal.
  • Goodwin, T., Evenhuis, C., Woodcock, S. and Quiroz, M. (2019). Bayesian Inference on the Keller–Segel Model. The ANZIAM Journal,  61:C181–C196. Journal.
  • Dang, K-D., Quiroz, M., Kohn, R., Tran, M-N. and Villani, M. (2019). Hamiltonian Monte Carlo with Energy Conserving Subsampling. Journal of Machine Learning Research, 20(100):1-31. Journal. ArXiv.
  • Quiroz, M., Kohn, R., Villani, M. and Tran, M-N.   (2019). Speeding up MCMC by Efficient Data Subsampling. Journal of the American Statistical Association, 114(526):831-843. Journal. ArXiv.
  • Xu, M., Quiroz, M., Kohn, R. and Sisson, S. A. (2019). Variance Reduction Properties of the Reparameterization Trick. In Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 2711-2720. Proceedings. ArXiv. Poster.
  • Quiroz, M., Villani, M., Kohn, R., Tran, M-N. and Dang, K-D. (2018). Subsampling MCMC – An Introduction for the Survey Statistician. Sankhya A, 80(1):33-69. Journal. ArXiv.
  • Quiroz, M., Tran, M-N., Villani, M. and Kohn, R. (2018). Speeding up MCMC by Delayed Acceptance and Data Subsampling. Journal of Computational and Graphical Statistics, 27(1):12-22. Journal. ArXiv.

Other Publications

  • Quiroz, M. and Tran, M.-N. (2023). Bayesian Analysis of Big Data via Subsampling Markov Chain Monte Carlo. In Wiley StatsRef: Statistics Reference Online (eds N. Balakrishnan, T. Colton, B. Everitt, W. Piegorsch, F. Ruggeri and J.L. Teugels). Wiley StatsRef.
  • Bayesian Inference in Large Data Problems. Doctoral Thesis. DiVA.

Unpublished work

  • The Block Pseudo-Marginal Sampler (with Minh-Ngoc Tran, Robert Kohn and Mattias Villani). ArXiv.
  • Dynamic Mixture-of-Experts Models for Longitudinal and Discrete-Time Survival Data (with Mattias Villani). SSRN. Revised paper here.