David J. Nott

Trans. Mach. Learn. Res., 2024

Flexible Variational Bayes Based on a Copula of a Mixture.

[BibT_eX]

[DOI]

David Gunawan

Robert Kohn

J. Comput. Graph. Stat., 2024

Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localization.

[BibT_eX]

[DOI]

David T. Frazier

J. Comput. Graph. Stat., 2024

Positional Encoder Graph Quantile Neural Networks for Geographic Data.

[BibT_eX]

[DOI]

William E. R. de Amorim

T. Rodrigues

Benedikt Lütke Schwienhorst

Guilherme S. Rodrigues

CoRR, 2024

Model-Free Local Recalibration of Neural Networks.

[BibT_eX]

[DOI]

CoRR, 2024

Dropout Regularization in Extended Generalized Linear Models Based on Double Exponential Families.

[BibT_eX]

[DOI]

Lucas Kock

Proceedings of the Machine Learning and Knowledge Discovery in Databases. Research Track, 2024

2023

Modularized Bayesian analyses and cutting feedback in likelihood-free inference.

[BibT_eX]

[DOI]

Atlanta Chakraborty

David T. Frazier

Stat. Comput., February, 2023

Correction to : Variational inference and sparsity in high-dimensional deep Gaussian mixture models.

[BibT_eX]

[DOI]

Lucas Kock

Stat. Comput., 2023

Misspecification-robust Sequential Neural Likelihood.

[BibT_eX]

[DOI]

CoRR, 2023

2022

Variational inference and sparsity in high-dimensional deep Gaussian mixture models.

[BibT_eX]

[DOI]

Lucas Kock

Stat. Comput., 2022

2021

Detecting conflicting summary statistics in likelihood-free inference.

[BibT_eX]

[DOI]

Stat. Comput., 2021

A Semiautomatic Method for History Matching Using Sequential Monte Carlo.

[BibT_eX]

[DOI]

Daniel Edward Pagendam

SIAM/ASA J. Uncertain. Quantification, 2021

Assessment and Adjustment of Approximate Inference Algorithms Using the Law of Total Variance.

[BibT_eX]

[DOI]

J. Comput. Graph. Stat., 2021

Marginally Calibrated Deep Distributional Regression.

[BibT_eX]

[DOI]

Michael Stanley Smith

J. Comput. Graph. Stat., 2021

2020

Conditionally structured variational Gaussian approximation with importance weights.

[BibT_eX]

[DOI]

Linda S. L. Tan

Aishwarya Bhaskaran

Stat. Comput., 2020

Likelihood-free approximate Gibbs sampling.

[BibT_eX]

[DOI]

G. S. Rodrigues

Stat. Comput., 2020

Robust Bayesian synthetic likelihood via a semi-parametric approach.

[BibT_eX]

[DOI]

Ziwen An

Stat. Comput., 2020

2018

Using History Matching for Prior Choice.

[BibT_eX]

[DOI]

Xueou Wang

Kerrie L. Mengersen

Michael Evans

Technometrics, 2018

Gaussian variational approximation with sparse precision matrices.

[BibT_eX]

[DOI]

Linda S. L. Tan

Stat. Comput., 2018

Variational Bayes with synthetic likelihood.

[BibT_eX]

[DOI]

Stat. Comput., 2018

Likelihood-free inference in high dimensions with synthetic likelihood.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2018

2017

Extending approximate Bayesian computation methods to high dimensions via a Gaussian copula model.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2017

2016

Variational inference for sparse spectrum Gaussian process regression.

[BibT_eX]

[DOI]

Stat. Comput., 2016

Functional regression approximate Bayesian computation for Gaussian process density estimation.

[BibT_eX]

[DOI]

G. S. Rodrigues

Comput. Stat. Data Anal., 2016

2014

Mixtures of experts for understanding model discrepancy in dynamic computer models.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2014

2012

The predictive Lasso.

[BibT_eX]

[DOI]

Minh-Ngoc Tran

Chenlei Leng

Stat. Comput., 2012

Variational approximation for heteroscedastic linear models and matching pursuit algorithms.

[BibT_eX]

[DOI]

Minh-Ngoc Tran

Chenlei Leng

Stat. Comput., 2012

The ensemble Kalman filter is an ABC algorithm.

[BibT_eX]

[DOI]

Lucy A. Marshall

Minh-Ngoc Tran

Stat. Comput., 2012

2011

Efficient MCMC Schemes for Computationally Expensive Posterior Distributions.

[BibT_eX]

[DOI]

Mark Fielding

Shie-Yui Liong

Technometrics, 2011

2010

A sign based loss approach to model selection in nonparametric regression.

[BibT_eX]

[DOI]

Jialiang Li

Stat. Comput., 2010

Bayesian projection approaches to variable selection in generalized linear models.

[BibT_eX]

[DOI]

Chenlei Leng

Comput. Stat. Data Anal., 2010

2008

Predictive performance of Dirichlet process shrinkage methods in linear regression.

[BibT_eX]

[DOI]

Comput. Stat. Data Anal., 2008

2007

A general approach to heteroscedastic linear regression.

[BibT_eX]

[DOI]

David S. Leslie

Robert Kohn

Stat. Comput., 2007

2006

Semiparametric estimation of mean and variance functions for non-Gaussian data.

[BibT_eX]

[DOI]

Comput. Stat., 2006

Deflection Routing on a Torus Is Monotone.

[BibT_eX]

[DOI]

Ana Busic

Jean-Michel Fourneau

Proceedings of the Positive Systems, 2006

2005

Efficient sampling schemes for Bayesian MARS models with many predictors.

[BibT_eX]

[DOI]

Anthony Y. C. Kuk

Hiep Duc

Stat. Comput., 2005

Convergence Routing under Bursty Traffic: Instability and an AIMD Controller.

[BibT_eX]

[DOI]

Jean-Michel Fourneau

Proceedings of the Second International Workshop on the Practical Application of Stochastic Modeling, 2005

2004

Mixed Routing for ROMEO Optical Burst.

[BibT_eX]

[DOI]

Jean-Michel Fourneau

Proceedings of the Computer and Information Sciences, 2004

2000

Multi-phase image modelling with excursion sets.

[BibT_eX]

[DOI]

Richard J. Wilson

Signal Process., 2000

1997

Parameter estimation for excursion set texture models.

[BibT_eX]

[DOI]