C. Holmes

发表

Bayesian auxiliary variable models for binary and multinomial regression

C. Holmes, L. Held, 2006 .

A Hierarchical Bayesian Framework for Constructing Sparsity-inducing Priors

A. Doucet, Anthony Lee, C. Holmes, 2010, 1009.1914.

Nonlinear estimation and classification

David D. Denison, B. Mallick, C. Holmes, 2003 .

Bayesian Nonparametrics: An invitation to Bayesian nonparametrics

P. Müller, C. Holmes, N. Hjort, 2010 .

Analyzing Nonstationary Spatial Data Using Piecewise Gaussian Processes

B. Mallick, C. Holmes, Hyoung-Moon Kim, 2005 .

Bayesian Radial Basis Functions of Variable Dimension

C. C. Homes, B. K. Mallick, B. Mallick, 1998, Neural Computation.

Bayesian Radial Basis Functions of Unknown Dimension

B. Mallick, C. Holmes, 1997 .

Bayesian Nonparametrics: Frontmatter

Christopher Holmes, Stephen G. Walker, Nils Lid Hjort, 2010 .

Two-sample Bayesian Nonparametric Hypothesis Testing

C. Holmes, J. Griffin, D. Stephens, 2009, 0910.5060.

On the marginal likelihood and cross-validation

C. Holmes, Edwin Fong, 2019, Biometrika.

Model-based geostatistics. Discussion. Authors' reply

T. C. Haas, M. Kenward, S. Nadarajah, 1998 .

A probabilistic nearest neighbour method for statistical pattern recognition

C. Holmes, N. Adams, 2002 .

Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach

Arnaud Doucet, Rémi Bardenet, Christopher C. Holmes, 2014, ICML.

A general framework for updating belief distributions

Pier Giovanni Bissiri, C. Holmes, S. Walker, 2013, Journal of the Royal Statistical Society. Series B, Statistical methodology.

Bayesian regression with multivariate linear splines

B. Mallick, C. Holmes, 2001 .

Assigning a value to a power likelihood in a general Bayesian model

C. Holmes, S. Walker, 2017, 1701.08515.

Approximate Models and Robust Decisions

C. Holmes, J. Watson, James A. Watson, 2014, 1402.6118.

Markov Chain Monte Carlo Methods and the Label Switching Problem in Bayesian Mixture Modeling

Ajay Jasra, David A. Stephens, Christopher Holmes, 2005 .

On Markov chain Monte Carlo methods for tall data

Arnaud Doucet, Rémi Bardenet, Christopher C. Holmes, 2015, J. Mach. Learn. Res..

Bayesian non‐parametric hidden Markov models with applications in genomics

C. Yau, G. Roberts, C. Holmes, 2011 .

MCMC and the Label Switching Problem in Bayesian Mixture Modelling 1 Markov Chain Monte Carlo Methods and the Label Switching Problem in Bayesian Mixture Modelling

C. Holmes, A. Jasra, D. Stephens, 2004 .

Bayesian Methods for Nonlinear Classification and Regressing

Christopher Holmes, Bani K. Mallick, Adrian Smith, 2002 .

Bayesian partition modelling

D. Hand, D. Denison, C. Holmes, 2002 .

Bayesian Prediction via Partitioning

D. Denison, B. Mallick, C. Holmes, 2005 .

A Bayesian nonparametric approach to testing for dependence between random variables

S. Filippi, C. Holmes, 2015, 1506.00829.

Likelihood inference in nearest‐neighbour classification models

Niall M. Adams, C. Holmes, N. Adams, 2003 .

Bayesian piecewise linear regression usingmultivariate linear splinesC

B. Mallick, C. Holmes, Febuary, 2007 .

Accounting for Model Uncertainty in Seemingly Unrelated Regressions

Bani K. Mallick, D. Denison, B. Mallick, 2002 .

Bayesian partitioning for classi cation and regressionC

D. Denison, B. Mallick, C. Holmes, 1999 .

Perfect simulation for Bayesian curve and surface ttingC

C. Holmes, K. B, MallickAbstractThis, 1999 .

An Adaptive Subsampling Approach for MCMC Inference in Large Datasets

Arnaud Doucet, Chris Holmes, Rémi Bardenet, 2014 .

Bayesian Nonparametrics: Principles and Practice Introduction

P. Müller, C. Holmes, N. Hjort, 2018 .

Multiscale Blind Source Separation

C. Holmes, A. Munk, Merle Behr, 2016, 1608.07173.

Perfect sampling for the wavelet reconstruction of signals

D. Denison, C. Holmes, 2002, IEEE Trans. Signal Process..

Supervised variable selection in randomised controlled trials prior to exploration of treatment effect heterogeneity: an example from severe malaria

C. Holmes, Chieh-Hsi Wu, 2019, 1901.03531.

Perfect sampling for the wavelet reconstruction of signals

David G. T. Denison, Chris Holmes, D. Denison, 2002, IEEE Trans. Signal Process..

Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior

Thomas E. Nichols, C. Holmes, H. Ganjgahi, 2022, 2206.09175.

A framework for adaptive MCMC targeting multimodal distributions

C. Holmes, K. Latuszy'nski, E. Pompe, 2018, The Annals of Statistics.

Density Estimation with Autoregressive Bayesian Predictives

C. Holmes, Edwin Fong, B. Lehmann, 2022, ArXiv.

Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior

Thomas E. Nichols, C. Holmes, H. Ganjgahi, 2022, 2206.09175.

Density Estimation with Autoregressive Bayesian Predictives

C. Holmes, Edwin Fong, B. Lehmann, 2022, ArXiv.

Better together? Statistical learning in models made of modules

Christian P. Robert, Pierre E. Jacob, Lawrence M. Murray, 2017, 1708.08719.

Minimum-Entropy Data Partitioning Using Reversible Jump Markov Chain Monte Carlo

Stephen J. Roberts, Christopher C. Holmes, Dave Denison, 2001, IEEE Trans. Pattern Anal. Mach. Intell..

Perfect Simulation Involving a Continuous andUnbounded State

C. Holmes, S. Guglielmi, Stephen G WalkerCNR-IAMI, 2000 .

Characterizing variation of nonparametric random probability measures using the Kullback–Leibler divergence

C. Holmes, L. Nieto-Barajas, J. Watson, 2017 .

Characterising variation of nonparametric random probability measures using the Kullback-Leibler divergence

C. Holmes, L. Nieto-Barajas, J. Watson, 2014, 1411.6578.

Bayesian Nonparametrics: List of contributors

Christopher Holmes, Stephen G. Walker, Nils Lid Hjort, 2010 .

Stochastic boosting algorithms

Ajay Jasra, Christopher C. Holmes, C. Holmes, 2011, Stat. Comput..

On population-based simulation for static inference

Ajay Jasra, Christopher C. Holmes, David A. Stephens, 2007, Stat. Comput..

Classification with Bayesian MARS

Christopher C. Holmes, Dave Denison, D. Denison, 2004, Machine Learning.

Generalized Nonlinear Modeling With Multivariate Free-Knot Regression Splines

B. Mallick, C. Holmes, 2003 .

Efficient simulation of Bayesian logistic regression models

Christopher Holmes, Leonhard Knorr-Held, C. Holmes, 2003 .

Bayesian model order determination and basis selectionfor seemingly unrelated regressionsC

D. Denison, B. Mallick, C. Holmes, 1999 .

Testing for dependence on tree structures

Christopher Holmes, Axel Munk, Merle Behr, 2019, Proceedings of the National Academy of Sciences.

Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures.

S. Filippi, C. Holmes, L. Nieto-Barajas, 2016, Electronic journal of statistics.

Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks.

François Caron, C. Holmes, F. Caron, 2015, Electronic journal of statistics.

Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo

Stephen J. Roberts, Christopher C. Holmes, Dave Denison, 2001, ICANN.

Nonparametric learning from Bayesian models with randomized objective functions

Stephen Walker, Simon Lyddon, Chris C. Holmes, 2018, NeurIPS.

Bayesian Partitioning for Estimating Disease Risk

D G Denison, C C Holmes, D. Denison, 2001, Biometrics.

Bayesian Sparsity-Path-Analysis of Genetic Association Signal using Generalized t Priors

Arnaud Doucet, Chris Holmes, Anthony Lee, 2011, Statistical applications in genetics and molecular biology.

General Bayesian updating and the loss-likelihood bootstrap

Chris Holmes, Simon Lyddon, Stephen Walker, 2017, Biometrika.

Accounting for control mislabeling in case-control biomarker studies.

Mattias Rantalainen, Chris C Holmes, C. Holmes, 2011, Journal of proteome research.

Principled Bayesian Minimum Divergence Inference

Jim Q. Smith, Jack Jewson, Christopher Holmes, 2018 .

Principles of Bayesian Inference Using General Divergence Criteria

Jim Q. Smith, Chris Holmes, Jack Jewson, 2018, Entropy.

Conformal Bayesian Computation

Chris Holmes, Edwin Fong, C. Holmes, 2021, NeurIPS.

Generalized monotonic regression using random change points

C. Holmes, N. Heard, 2003, Statistics in medicine.

CHAPTER 8 – The General Linear Model

S. J. Kiebel, A. P. Kherif, C. Holmes, 2007 .

Martingale posterior distributions

Stephen G. Walker, Chris Holmes, Edwin Fong, 2021, 2103.15671.

On the Utility of Graphics Cards to Perform Massively Parallel Simulation of Advanced Monte Carlo Methods

Arnaud Doucet, Anthony Lee, Christopher Yau, 2009, Journal of computational and graphical statistics : a joint publication of American Statistical Association, Institute of Mathematical Statistics, Interface Foundation of North America.

Perfect Simulation for orthogonal model mixing

Christopher Holmes, Bani K. Mallick, B. Mallick, 1998 .

On the Stability of General Bayesian Inference

Jim Q. Smith, C. Holmes, Jack Jewson, 2023, 2301.13701.

Foundations of Bayesian Learning from Synthetic Data pdf

Chris Holmes, Harrison Wilde, Jack Jewson, 2020, AISTATS.

Population-Based Reversible Jump Markov Chain Monte Carlo

Ajay Jasra, David A. Stephens, Chris C. Holmes, 2007, 0711.0186.

Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates

C. Holmes, Edwin Fong, B. Lehmann, 2022, UAI.

Interacting sequential Monte Carlo samplers for trans-dimensional simulation

Arnaud Doucet, Ajay Jasra, Christopher C. Holmes, 2008, Comput. Stat. Data Anal..

A boosting approach to structure learning of graphs with and without prior knowledge

Arnaud Doucet, Christopher C. Holmes, Shahzia Anjum, 2009, Bioinform..

Bayesian Lesion Estimation with a Structured Spike-and-Slab Prior

Thomas E. Nichols, C. Holmes, H. Ganjgahi, 2022, Journal of the American Statistical Association.

Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap

Christopher C. Holmes, Edwin Fong, Simon Lyddon, 2019, ICML.

Statistical Applications in Genetics and Molecular Biology Bayesian Sparsity-path-analysis of Genetic Association Signal Using Generalized T Priors Bayesian Sparsity-path-analysis of Genetic Association Signal Using Generalized T Priors

A. Doucet, Anthony Lee, C. Holmes, 2022 .

Bayesian auxiliary variable models for binary and multinomial regression

C. Holmes, L. Held, 2006 .