Chris Holmes

Chris Holmes

Decision theory, biostatistics and precision medicine, probabilistic learning under model misspecification

I am Professor of Biostatistics and MRC Programme Leader in Statistical Genomics. I hold a joint appointment in the Department of Statistics and the Nuffield Department of Medicine, University of Oxford. I am a Faculty Fellow of the Alan Turing Institute. I have broad research interests in the theory, methods, and applications of decision analysis, probabilistic modelling, and statistical machine learning in medical research.

Publications

2017

  • J. Watson, L. Nieto-Barajas, C. C. Holmes, Characterizing variation of nonparametric random probability measures using the Kullback–Leibler divergence, Statistics, vol. 51, no. 3, 558–571, 2017.
  • S. Filippi, C. C. Holmes, . others, A Bayesian nonparametric approach to testing for dependence between random variables, Bayesian Analysis, 2017.
  • A. R. Taylor, J. A. Flegg, C. C. Holmes, P. J. Guérin, C. H. Sibley, M. D. Conrad, G. Dorsey, P. J. Rosenthal, Artemether-Lumefantrine and Dihydroartemisinin-Piperaquine Exert Inverse Selective Pressure on Plasmodium Falciparum Drug Sensitivity-Associated Haplotypes in Uganda, in Open forum infectious diseases, 2017, vol. 4, no. 1.
  • G. Nicholson, C. C. Holmes, A note on statistical repeatability and study design for high-throughput assays, Statistics in medicine, vol. 36, no. 5, 790–798, 2017.
  • C. Holmes, S. Walker, Assigning a value to a power likelihood in a general Bayesian model, Biometrika, vol. 104, no. 2, 497–503, 2017.
  • T. Rukat, C. C. Holmes, M. K. Titsias, C. Yau, Bayesian Boolean Matrix Factorisation, arXiv preprint arXiv:1702.06166, 2017.
  • C. C. Drovandi, C. C. Holmes, J. McGree, K. Mengersen, S. Richardson, E. Ryan, Principles of experimental design for Big Data analysis, Statistical Science, 2017.
  • I. Roxanis, R. Colling, E. A. Rakha, A. Green, J. Rittscher, R. C. Conceicao, A. Ross, G. Nicholson, C. C. Holmes, Digital Analysis of Tumour Microarchitecture as an Independent Prognostic Tool in Breast Cancer, in LABORATORY INVESTIGATION, 2017, vol. 97, 68A–68A.
  • A. Doucet, C. Holmes, R. Bardenet, On Markov chain Monte Carlo Methods for Tall Data, 2017.
  • T. Rukat, C. C. Holmes, M. K. Titsias, C. Yau, Bayesian Boolean Matrix Factorisation, 2017.

2016

  • S. Filippi, C. C. Holmes, L. E. Nieto-Barajas, Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures, Electronic Journal of Statistics, 2016.
  • P. G. Bissiri, C. Holmes, S. G. Walker, A general framework for updating belief distributions, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2016.
  • M. K. Titsias, C. C. Holmes, C. Yau, Statistical inference in hidden Markov models using k-segment constraints, Journal of the American Statistical Association, vol. 111, no. 513, 200–215, 2016.
  • J. Watson, C. C. Holmes, . others, Approximate models and robust decisions, Statistical Science, vol. 31, no. 4, 465–489, 2016.
  • T. Gray-Davies, C. C. Holmes, F. Caron, . others, Scalable Bayesian nonparametric regression via a Plackett-Luce model for conditional ranks, Electronic Journal of Statistics, vol. 10, no. 2, 1807–1828, 2016.
  • S. Filippi, C. C. Holmes, L. E. Nieto-Barajas, . others, Scalable Bayesian nonparametric measures for exploring pairwise dependence via Dirichlet Process Mixtures, Electronic Journal of Statistics, vol. 10, no. 2, 3338–3354, 2016.
  • Z. Wang, J. S. Morris, C. C. Holmes, J. Ahn, B. Li, W. Lu, X. Tang, I. I. Wistuba, W. Wang, Cell type-specific deconvolution of heterogeneous tumor samples with immune infiltration using expression data. American Association for Cancer Research, 2016.
  • M. Behr, C. C. Holmes, A. Munk, Multiscale Blind Source Separation, arXiv preprint arXiv:1608.07173, 2016.
  • J. Watson, C. C. Holmes, . others, Rejoinder: Approximate Models and Robust Decisions, Statistical Science, vol. 31, no. 4, 516–520, 2016.

2015

  • C. C. Holmes, F. Caron, J. E. Griffin, D. A. Stephens, Two-sample Bayesian nonparametric hypothesis testing, Bayesian Analysis, vol. 10, no. 2, 297–320, 2015.
  • C. C. Holmes, F. Caron, J. E. Griffin, D. A. Stephens, . others, Two-sample Bayesian nonparametric hypothesis testing, Bayesian Analysis, vol. 10, no. 2, 297–320, 2015.
  • R. Bardenet, A. Doucet, C. C. Holmes, On Markov chain Monte Carlo methods for tall data, arXiv preprint arXiv:1505.02827, 2015.
  • C. C. Drovandi, C. C. Holmes, J. McGree, K. Mengersen, S. Richardson, E. Ryan, A principled experimental design approach to Big Data analysis, 2015.
  • R. G. Stiphout, L. Winchester, S. A. Haider, J. Ragoussis, A. L. Harris, C. C. Holmes, F. M. Buffa, . others, Abstract B1-56: Distinct roles of copy number and loss-of-heterozygosity in predicting prognosis for breast cancer patients. American Association for Cancer Research, 2015.
  • A. C. Daly, D. J. Gavaghan, C. C. Holmes, J. Cooper, Hodgkin–Huxley revisited: reparametrization and identifiability analysis of the classic action potential model with approximate Bayesian methods, Royal Society open science, vol. 2, no. 12, 150499, 2015.
  • C. Holmes, P. Bissiri, S. Walker, A general framework for updating belief distributions, Journal of the Royal Statistical Society Series B: Statistical Methodology, 2015.

2014

  • R. Bardenet, A. Doucet, C. C. Holmes, Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach, in Proceedings of the 31st International Conference on Machine Learning (ICML-14), 2014, 405–413.
  • R. Bardenet, A. Doucet, C. C. Holmes, An adaptive subsampling approach for MCMC inference in large datasets, in Proceedings of The 31st International Conference on Machine Learning, 2014, 405–413.

2013

  • D. D. Denison, M. H. Hansen, C. C. Holmes, B. Mallick, B. Yu, Nonlinear estimation and classification. Springer Science & Business Media, 2013.
  • Q. F. Wills, K. J. Livak, A. J. Tipping, T. Enver, A. J. Goldson, D. W. Sexton, C. C. Holmes, Single-cell gene expression analysis reveals genetic associations masked in whole-tissue experiments, Nature biotechnology, vol. 31, no. 8, 748–752, 2013.
  • W. Wang, V. Baladandayuthapani, C. C. Holmes, K. Do, Integrative network-based Bayesian analysis of diverse genomics data, BMC bioinformatics, vol. 14, no. 13, S8, 2013.

2012

  • A. Lee, F. Caron, A. Doucet, C. C. Holmes, . others, Bayesian sparsity-path-analysis of genetic association signal using generalized t priors, Statistical applications in genetics and molecular biology, vol. 11, no. 2, 1–29, 2012.
  • F. Caron, C. C. Holmes, E. Rio, On the sampling distribution of an $\backslash ell\^ 2$ distance between Empirical Distribution Functions with applications to nonparametric testing, PhD thesis, INRIA, 2012.
  • J. Cazier, C. C. Holmes, J. Broxholme, GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples, Bioinformatics, vol. 28, no. 22, 2981–2982, 2012.
  • A. R. Taylor, J. A. Flegg, P. J. Guerin, C. Roper, C. C. Holmes, A Bayesian model for estimating with-in host P. falciparum haplotype frequencies, Malaria Journal, vol. 11, no. S1, P36, 2012.
  • M. Rantalainen, C. C. Holmes, Robust Statistical Methods For Genome-Wide Eqtl Analysis, 2012.
  • F. Caron, C. C. Holmes, E. Rio, On the sampling distribution of an l2 norm of the Empirical Distribution Function, with applications to two-sample nonparametric testing, 2012.
  • C. C. Holmes, Auxiliary Counting Variables for Posterior Decoding of Hidden Markov Models with Applications to Cancer Genomics, in ISBA Regional Meeting and International Workshop/Conference on Bayesian Theory and Applications (IWCBTA), 2012.
  • C. C. Holmes, Large-scale genetic analysis of quantitative traits, PhD thesis, University of Oxford, 2012.
  • C. C. Holmes, Extensions of the case-control design in genome-wide association studies, PhD thesis, University of Oxford, 2012.

2011

  • C. Yau, C. C. Holmes, Hierarchical Bayesian nonparametric mixture models for clustering with variable relevance determination, Bayesian analysis (Online), vol. 6, no. 2, 329, 2011.
  • B. S. Kato, G. Nicholson, M. Neiman, M. Rantalainen, C. C. Holmes, A. Barrett, M. Uhlén, P. Nilsson, T. D. Spector, J. M. Schwenk, Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model, Proteome science, vol. 9, no. 1, 73, 2011.
  • N. Cardin, C. C. Holmes, P. Donnelly, J. Marchini, Bayesian hierarchical mixture modeling to assign copy number from a targeted CNV array, Genetic epidemiology, vol. 35, no. 6, 536–548, 2011.
  • C. C. Holmes, L. Held, . others, Response to van der Lans, Bayesian Analysis, vol. 6, no. 2, 357–358, 2011.
  • A. Drong, G. Nicholson, M. Schuster, F. Karpe, M. McCarthy, C. Holmes, M. Rantalainen, C. Lindgren, M. Consortia, The presence of methylation quantitative trait loci indicate a direct genetic influence on the level of methylation in adipose tissue, 2011.
  • J. G. Ciampa, C. C. Holmes, N. Chatterjee, Application of a novel multi-locus test for genetic association incorporating gene-gene interaction suggests functionality for multiple susceptibility loci for prostate cancer. American Association for Cancer Research, 2011.

2010

  • N. L. Hjort, C. C. Holmes, P. Müller, S. G. Walker, Bayesian nonparametrics. Cambridge University Press, 2010.
  • M. A. Suchard, C. C. Holmes, M. West, Some of the what?, why?, how?, who? and where? of graphics processing unit computing for Bayesian analysis, Bulletin of the International Society for Bayesian Analysis, vol. 17, no. 1, 12–16, 2010.
  • A. Lee, F. Caron, A. Doucet, C. C. Holmes, A hierarchical Bayesian framework for constructing sparsity-inducing priors, arXiv preprint arXiv:1009.1914, 2010.
  • N. L. Hjort, C. C. Holmes, P. Müller, S. G. Walker, An invitation to Bayesian nonparametrics, Bayesian Nonparametrics, vol. 28, 1, 2010.
  • J. Griffin, C. C. Holmes, Computational issues arising in Bayesian nonparametric hierarchical models, Bayesian Nonparametrics, vol. 28, 208, 2010.
  • C. Yau, D. Mouradov, R. N. Jorissen, S. Colella, G. Mirza, G. Steers, A. Harris, J. Ragoussis, O. Sieber, C. C. Holmes, . others, A statistical approach for detecting genomic aberrations in heterogeneous tumor samples from single nucleotide polymorphism genotyping data, Genome biology, vol. 11, no. 9, R92, 2010.
  • A. Agam, B. Yalcin, A. Bhomra, M. Cubin, C. Webber, C. C. Holmes, J. Flint, R. Mott, Elusive copy number variation in the mouse genome, PLoS One, vol. 5, no. 9, e12839, 2010.
  • N. L. Hjort, C. C. Holmes, P. Müller, S. G. Walker, Bayesian nonparametrics. Cambridge series in statistical and probabilistic mathematics, Cambridge: Cambridge Univ. Press. Mathematical Reviews (MathSciNet): MR2722987, 2010.
  • A. Timbs, S. Knight, E. SadighiAkha, A. Burns, H. Dreau, A. Hewitt, C. Hatton, C. Yau, C. C. Holmes, J. Taylor, . others, Quantitative Whole Genome Analysis of Sequential Samples From Patients with B-CLL Identifies Novel Recurrent Copy Number Alterations Involving Critical B-Cell Transcription Factors, Blood, vol. 116, no. 21, 3590–3590, 2010.
  • Q. Zhou, A. K. Ching, W. K. Leung, C. Szeto, S. Ho, C. C. Holmes, Y. Yuan, P. B. Lai, W. Yeo, N. Wong, Novel therapeutic potential in targeting the microtubules by nanoparticle albumin-bound paclitaxel in hepatocellular carcinoma. American Association for Cancer Research, 2010.

2009

  • J. E. Lemieux, N. Gomez-Escobar, A. Feller, C. Carret, A. Amambua-Ngwa, R. Pinches, F. Day, S. A. Kyes, D. J. Conway, C. C. Holmes, . others, Statistical estimation of cell-cycle progression and lineage commitment in Plasmodium falciparum reveals a homogeneous pattern of transcription in ex vivo culture, Proceedings of the National Academy of Sciences, vol. 106, no. 18, 7559–7564, 2009.
  • J. W. Klingelhoefer, L. Moutsianas, C. C. Holmes, Approximate Bayesian feature selection on a large meta-dataset offers novel insights on factors that effect siRNA potency, Bioinformatics, vol. 25, no. 13, 1594–1601, 2009.
  • C. C. Holmes, A. Jasra, Antithetic methods for gibbs samplers, Journal of Computational and Graphical Statistics, vol. 18, no. 2, 401–414, 2009.
  • W. Valdar, C. C. Holmes, R. Mott, J. Flint, Mapping in structured populations by resample model averaging, Genetics, vol. 182, no. 4, 1263–1277, 2009.
  • J. E. Lemieux, A. Feller, C. C. Holmes, C. I. Newbold, Reply to Wirth et al.: In vivo profiles show continuous variation between 2 cellular populations, Proceedings of the National Academy of Sciences, vol. 106, no. 27, E71–E72, 2009.
  • C. C. Holmes, Increasing statistical power and generalizability in genomics microarray research, PhD thesis, University of Oxford, 2009.

2008

  • A. Ramasamy, A. Mondry, C. C. Holmes, D. G. Altman, Key issues in conducting a meta-analysis of gene expression microarray datasets, PLoS Med, vol. 5, no. 9, e184, 2008.
  • T. W. Chittenden, E. A. Howe, A. C. Culhane, R. Sultana, J. M. Taylor, C. C. Holmes, J. Quackenbush, Functional classification analysis of somatically mutated genes in human breast and colorectal cancers, Genomics, vol. 91, no. 6, 508–511, 2008.
  • C. Yau, C. Holmes, CNV discovery using SNP genotyping arrays, Cytogenetic and genome research, vol. 123, no. 1-4, 307–312, 2008.

2007

  • P. Dellaportas, D. G. Denison, C. C. Holmes, Flexible threshold models for modelling interest rate volatility, Econometric reviews, vol. 26, no. 2-4, 419–437, 2007.
  • C. C. Holmes, A. Pintore, BAYESIAN STATISTICS 8, pp. 253-282. JM Bernardo, MJ Bayarri, JO Berger, AP Dawid, D. Heckerman, AFM Smith and M. West (Eds.)\copyright Oxford University Press, 2007, in Bayesian statistics 8: proceedings of the eighth Valencia International Meeting, June 2-6, 2006, 2007, vol. 8, 253.
  • L. Astle, C. Holmes, D. Balding, Turbo Genomic Control, 2007.
  • S. Colella, C. Yau, J. M. Taylor, G. Mirza, H. Butler, P. Clouston, A. S. Bassett, A. Seller, C. C. Holmes, J. Ragoussis, QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data, Nucleic Acids Research, vol. 35, no. 6, 2013–2025, 2007.
  • J. Griffin, C. Holmes, Bayesian nonparametric calibration with applications in spatial epidemiology, Technical Report, Institute of Mathematics, Statistics and Actuarial Science, University of Kent, 2007.
  • M. Zucknick, C. C. Holmes, S. Richardson, Mcmc Methods for Bayesian Variable Selection in Large-scale Genomic Applications, Annals of Human Genetics, vol. 71, no. 4, 558–559, 2007.

2006

  • C. C. Holmes, L. Held, . others, Bayesian auxiliary variable models for binary and multinomial regression, Bayesian analysis, vol. 1, no. 1, 145–168, 2006.
  • J. Stephenson, K. Gallagher, C. C. Holmes, A Bayesian approach to calibrating apatite fission track annealing models for laboratory and geological timescales, Geochimica et Cosmochimica Acta, vol. 70, no. 20, 5183–5200, 2006.
  • H. De Wet, M. Allen, C. C. Holmes, M. Stobbart, J. D. Lippiat, H. De Wet, M. Allen, C. C. Holmes, M. Stobbart, J. D. Lippiat, . others, Modulation of the BK channel by estrogens: examination at single channel level, Molecular membrane biology, vol. 23, no. 5, 420–429, 2006.
  • V. Baladandayuthapani, C. C. Holmes, B. Mallick, R. Carroll, Modeling nonlinear gene interactions using Bayesian MARS. Bayesian Inference for Gene Expression and Proteomics. Cambridge University Press, 2006.
  • K. Gallagher, A. Jasra, D. Stephens, C. C. Holmes, A new approach to mixture modelling for geochronology, Geochimica et Cosmochimica Acta, vol. 70, no. 18, A190, 2006.
  • A. Jasra, D. Stephens, K. Gallagher, C. Holmes, Analysis of geochronological data with measurement error using Bayesian mixtures, Mathematical Geology, vol. 38, 269–300, 2006.
  • N. A. Heard, C. C. Holmes, D. A. Stephens, A quantitative study of gene regulation involved in the immune response of anopheline mosquitoes, Journal of the American Statistical Association, vol. 101, no. 473, 18–29, 2006.
  • J. Stephenson, K. Gallagher, C. Holmes, Low temperature thermochronology and strategies for multiple samples: 2: Partition modelling for 2d/3d distributions with discontinuities, Earth and Planetary Science Letters, vol. 241, no. 3, 557–570, 2006.
  • V. Baladandayuthapani, C. C. Holmes, B. K. Mallick, R. J. Carroll, Bayesian Inference for Gene Expression and Proteomics: Modeling Nonlinear Gene Interactions Using Bayesian MARS, 2006.

2005

  • H. Kim, B. K. Mallick, C. Holmes, Analyzing nonstationary spatial data using piecewise Gaussian processes, Journal of the American Statistical Association, vol. 100, no. 470, 653–668, 2005.
  • K. Gallagher, J. Stephenson, R. Brown, C. C. Holmes, P. Ballester, Exploiting 3D spatial sampling in inverse modeling of thermochronological data, Reviews in mineralogy and geochemistry, vol. 58, no. 1, 375–387, 2005.
  • J. Stephenson, C. C. Holmes, K. Gallagher, A. Pintore, A statistical technique for modelling non-stationary spatial processes, Geostatistics Banff 2004, 125–134, 2005.
  • K. Gallagher, J. Stephenson, R. Brown, C. C. Holmes, P. Fitzgerald, Low temperature thermochronology and modeling strategies for multiple samples 1: Vertical profiles, Earth and Planetary Science Letters, vol. 237, no. 1, 193–208, 2005.
  • A. Jasra, C. C. Holmes, D. A. Stephens, Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling, Statistical Science, 50–67, 2005.
  • N. A. Heard, C. C. Holmes, D. A. Stephens, D. J. Hand, G. Dimopoulos, Bayesian coclustering of Anopheles gene expression time series: study of immune defense response to multiple experimental challenges, Proceedings of the National Academy of Sciences of the United States of America, vol. 102, no. 47, 16939, 2005.
  • C. Holmes, D. T. Denison, S. Ray, B. Mallick, Bayesian prediction via partitioning, Journal of Computational and Graphical Statistics, vol. 14, no. 4, 811–830, 2005.
  • C. C. Holmes, S. D. Brown, All systems GO for understanding mouse gene function, The Scientist, vol. 19, no. 1, 20–1, 2005.

2004

  • C. C. Holmes, S. D. Brown, All systems GO for understanding mouse gene function, Journal of biology, vol. 3, no. 5, 20, 2004.
  • J. Stephenson, K. Gallagher, C. Holmes, Beyond kriging: dealing with discontinuous spatial data fields using adaptive prior information and Bayesian partition modelling, Geological Society, London, Special Publications, vol. 239, no. 1, 195–209, 2004.

2003

  • C. Holmes, L. Held, On the simulation of Bayesian binary and polychotomous regression models using auxiliary variables, Technical report. Available at: http://www. stat. uni-muenchen. de/\\~ leo, 2003.
  • C. Holmes, N. Heard, Generalized monotonic regression using random change points, Statistics in Medicine, vol. 22, no. 4, 623–638, 2003.
  • C. Holmes, B. Mallick, Generalized nonlinear modeling with multivariate free-knot regression splines, Journal of the American Statistical Association, vol. 98, no. 462, 352–368, 2003.
  • C. C. Holmes, N. M. Adams, Likelihood inference in nearest-neighbour classification models, Biometrika, 99–112, 2003.
  • C. Holmes, D. Denison, Classification with bayesian MARS, Machine Learning, vol. 50, no. 1, 159–173, 2003.
  • C. Holmes, B. Mallick, Perfect simulation for Bayesian curve and surface fitting, Preprint from www. stat. tamu. edu/\\~ bmallick/papers/perf. ps, 2003.
  • R. Graziani, C. C. Holmes, Bayesian free knot polynomial splines of random order. Università commerciale Luigi Bocconi, 2003.
  • R. M. Gray, D. Denison, M. Hansen, C. Holmes, B. Mallick, B. Yu, Gauss mixture quantization: clustering Gauss mixtures, in Nonlinear Estimation and Classification, 2003, vol. 1003, 189–212.
  • C. Holmes, D. Denison, Stochastic search algorithms inspired by physical and biological systems are applied to the problem of learning directed graphical probability models in the presence of missing observations and hidden variables. For this class of problems, deterministic search algorithms tend to halt at local optima, requiring random restarts to obtain solutions of acceptable quality. We compare three stochastic search..., Machine Learning, vol. 50, no. 3, 279–301, 2003.

2002

  • C. C. Holmes, D. G. Denison, Perfect sampling for the wavelet reconstruction of signals, IEEE Transactions on Signal Processing, vol. 50, no. 2, 337–344, 2002.
  • A. Guglielmi, C. C. Holmes, S. G. Walker, Perfect simulation involving functionals of a Dirichlet process, Journal of Computational and Graphical Statistics, vol. 11, no. 2, 306–310, 2002.
  • D. Denison, N. Adams, C. Holmes, D. Hand, Bayesian partition modelling, Computational statistics & data analysis, vol. 38, no. 4, 475–485, 2002.
  • J. Ferreira, D. Denison, C. Holmes, Partition modelling, 2002.
  • C. Holmes, N. Adams, A probabilistic nearest neighbour method for statistical pattern recognition, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 64, no. 2, 295–306, 2002.
  • C. Holmes, D. T. Denison, B. Mallick, Accounting for model uncertainty in seemingly unrelated regressions, Journal of Computational and Graphical Statistics, vol. 11, no. 3, 533–551, 2002.
  • C. Holmes, [Spline Adaptation in Extended Linear Models]: Comment, Statistical Science, vol. 17, no. 1, 22–24, 2002.

2001

  • C. Holmes, B. Mallick, Bayesian regression with multivariate linear splines, Journal of the Royal Statistical Society: Series B (Statistical Methodology), vol. 63, no. 1, 3–17, 2001.
  • D. Denison, C. Holmes, Bayesian partitioning for estimating disease risk, Biometrics, vol. 57, no. 1, 143–149, 2001.
  • S. J. Roberts, C. C. Holmes, D. Denison, Minimum-entropy data partitioning using reversible jump Markov chain Monte Carlo, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, no. 8, 909–914, 2001.
  • S. Roberts, C. C. Holmes, D. Denison, Minimum-entropy data clustering using reversible jump markov chain monte carlo, Artificial Neural Networks—ICANN 2001, 103–110, 2001.
  • C. C. D. L. Holmes, Bayesian methods for nonlinear classification and regression, PhD thesis, Department of Mathematics, Imperial College, 2001.

2000

  • C. C. Holmes, B. K. Mallick, Bayesian wavelet networks for nonparametric regression, IEEE transactions on neural networks, vol. 11, no. 1, 27–35, 2000.

1999

  • A. Guglielmi, C. C. Holmes, S. G. Walker, Perfect simulation involving a continuous and unbounded state space, Preprint, 1999.
  • C. Holmes, D. Denison, Bayesian wavelet analysis with a model complexity prior, Bayesian statistics, vol. 6, 769–776, 1999.
  • C. Holmes, D. Denison, B. Mallick, Bayesian partitioning for classification and regression, Manuscript, Imperial College, 1999.
  • C. Holmes, B. Mallick, Generalised nonlinear modelling with multivariate smoothing splines, Unpublished manuscript, Statistics Section, Department of Mathematics, Imperial College of London, 1999.

1998

  • C. Holmes, B. Mallick, Bayesian radial basis functions of variable dimension, Neural Computation, vol. 10, no. 5, 1217–1233, 1998.
  • C. Holmes, B. Mallick, Parallel Markov chain Monte Carlo sampling: an evolutionary based approach, London, Imperial College, 1998.

1997

  • C. Holmes, B. Mallick, Bayesian radial basis functions of unknown dimension, Imperial College Report, 1997.