User profiles for Hien Duy Nguyen

Hien Duy Nguyen

La Trobe University and Kyushu University
Verified email at latrobe.edu.au
Cited by 1441

[HTML][HTML] Approximations of conditional probability density functions in Lebesgue spaces via mixture of experts models

HD Nguyen, TT Nguyen, F Chamroukhi… - Journal of Statistical …, 2021 - Springer
Mixture of experts (MoE) models are widely applied for conditional probability density
estimation problems. We demonstrate the richness of the class of MoE models by proving …

Passive superconducting circulator on a chip

R Navarathna, DT Le, AR Hamann, HD Nguyen… - Physical review …, 2023 - APS
An on-chip microwave circulator that is compatible with superconducting devices is a key
element for scale up of superconducting circuits. Previous approaches to integrating circulators …

Approximate Bayesian computation via the energy statistic

HD Nguyen, J Arbel, H Lü, F Forbes - IEEE Access, 2020 - ieeexplore.ieee.org
Approximate Bayesian computation (ABC) has become an essential part of the Bayesian
toolbox for addressing problems in which the likelihood is prohibitively expensive or entirely …

Functional connectivity subtypes associate robustly with ASD diagnosis

…, A Tam, P Orban, C Moreau, Y Benhajali, HD Nguyen… - Elife, 2022 - elifesciences.org
Our understanding of the changes in functional brain organization in autism is hampered by
the extensive heterogeneity that characterizes this neurodevelopmental disorder. Data …

[PDF][PDF] A non-asymptotic penalization criterion for model selection in mixture of experts models

TT Nguyen, HD Nguyen, F Chamroukhi… - arXiv preprint arXiv …, 2021 - researchgate.net
Mixture of experts (MoE) is a popular class of models in statistics and machine learning that
has sustained attention over the years, due to its flexibility and effectiveness. We consider …

A non-asymptotic risk bound for model selection in a high-dimensional mixture of experts via joint rank and variable selection

T Nguyen, DN Nguyen, HD Nguyen… - … Joint Conference on …, 2023 - Springer
We are motivated by the problem of identifying potentially nonlinear regression relationships
between high-dimensional outputs and high-dimensional inputs of heterogeneous data. …

A non-asymptotic approach for model selection via penalization in high-dimensional mixture of experts models

TT Nguyen, HD Nguyen, F Chamroukhi… - Electronic Journal of …, 2022 - projecteuclid.org
Mixture of experts (MoE) are a popular class of statistical and machine learning models that
have gained attention over the years due to their flexibility and efficiency. In this work, we …

Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors

F Forbes, HD Nguyen, TT Nguyen, J Arbel - Statistics and Computing, 2022 - Springer
A key ingredient in approximate Bayesian computation (ABC) procedures is the choice of a
discrepancy that describes how different the simulated and observed data are, often based …

[PDF][PDF] Approximate Bayesian computation with surrogate posteriors

F Forbes, HD Nguyen, TT Nguyen, J Arbel - Preprint hal, 2021 - hal.science
A key ingredient in approximate Bayesian computation (ABC) procedures is the choice of a
discrepancy that describes how different the simulated and observed data are, often based …

Non-asymptotic model selection in block-diagonal mixture of polynomial experts models

TT Nguyen, F Chamroukhi, HD Nguyen… - arXiv preprint arXiv …, 2021 - arxiv.org
Model selection, via penalized likelihood type criteria, is a standard task in many statistical
inference and machine learning problems. Progress has led to deriving criteria with …