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Journal publications

  • Hien D. Nguyen, Julyan Arbel, Hongliang Lu, and Florence Forbes. Approximate Bayesian computation via the energy statistic, IEEE Access 2020, p.1-16, (pdf)
  • Mariia Vladimirova, Stéphane Girard, Hien D. Nguyen, and Julyan Arbel. Sub-Weibull distributions: generalizing sub-Gaussian and sub-Exponential properties to heavier-tailed distributions. Stat, 2020. [ arXiv ]
  • Nguyen, T., Nguyen, H. D., Chamroukhi, F., & McLachlan, G.J. Approximation by finite mixtures of continuous density functions that vanish at infinity, Cogent Mathematics and Statistics, April 2020, (pdf)
  • Redivo, E., Nguyen, H. D., and Gupta, M. . Bayesian clustering of skewed and multimodal data using geometric skew normal distributions. Computational Statistics and Data Analysis,  2020.
  • Hien D. Nguyen, Faicel Chamroukhi, Florence Forbes. Approximation results regarding the multiple-output Gaussian gated mixture of linear experts model. Neurocomputing, Elsevier, 2019, (pdf)
  • Julyan Arbel, Olivier Marchal, and Hien D Nguyen. On strict sub-Gaussianity, optimal proxy variance and symmetry for bounded random variables. ESAIM: Probability & Statistics, forthcoming, 2020.DOI | arXiv | HAL ]
  • Chamroukhi F, Nguyen H.D. Model-based clustering and classification of functional data.  Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery.  9. 2019, (pdf)
  • Hien D. Nguyen, Florence Forbes and Geoffrey J. McLachlan. Mini-batch learning of exponential family finite mixture models,  Statistics and Computing, 2020 (pdf)

Conference publications

  • Hien D. Nguyen, Julyan Arbel, Hongliang Lu, and Florence Forbes. Approximate Bayesian Computation with surrogate posteriors. UQ2021, Dallas, Tx USA (online).
  • J.-B. Durand, F. Forbes, C.D. Phan, L. Truong, H.D. Nguyen, F. Dama. Spatial segmentation of count data with a Bayesian nonparametric Hidden Markov model: application to traffic crash risk mapping. JDS 2021 : 52emes Journees de Statistique de la Societe Francaise de Statistique, Jun 2021, Nice, France.
  • Chamroukhi, F., Lecocq, F., & Nguyen, H. D. Regularized estimation and feature selection in mixtures of Gaussian-gated experts models. In Nguyen H. (eds) Statistics and Data Science. Proc. Research School on Statistics and Data Science (RSSDS), July 2019, Melbourne, Australia. Communications in Computer and Information Science, vol 1150. Springer,
  • F. Forbes, A. Arnaud, B. Lemasson, E. Barbier. Component Elimination Strategies to Fit Mixtures of Multiple Scale Distributions. In: Nguyen H. (eds) Statistics and Data Science.  Proc. Research School on Statistics and Data Science (RSSDS), July 2019, Melbourne, Australia. Communications in Computer and Information Science, vol 1150. Springer, (slides), (pdf)

Working papers

  • Mohsen Maleki, Darren Wraith and Florence Forbes. Finite mixtures of multiple scaled Generalized Hyperbolic distributions using a Bayesian approach.
  • Antoine Usseglio-Carleve, Hien D. Nguyen, S. Girard. Development of majorization-minimization algorithms for the computation of empirical and theoretical geometric multivariate expectiles.
  • Jean-Baptiste Durand, Florence Forbes, Hien D. Nguyen, C. D. Phan and Long Truong. Bayesian non parametric spatial prior for car crash risk mapping: a case study in Melbourne, Australia.
  • Florence Forbes, Hien D. Nguyen, Tin Trung Nguyen, Julyan Arbel. Approximate Bayesian Computation with surrogate posteriors.
  • Julyan Arbel, Stéphane Girard, Hien D. Nguyen, Antoine Usseglio-Carleve. Multivariate expectile-based distribution.
  • H. D. Nguyen, F. Forbes. Global implicit function theorems and the online expectation-maximisation algorithm.
  • TrungTin Nguyen, Faicel Chamroukhi, Hien Duy Nguyen, Florence Forbes. A non-asymptotic model selection in block-diagonal mixture of polynomial experts models.
  • TrungTin Nguyen, Faicel Chamroukhi, Hien Duy Nguyen, Florence Forbes. A non-asymptotic penalization criterion for model selection in mixture of experts models.

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