Christopher C. Holmes

Publication Activity (10 Years)

Years Active: 2000-2024
Publications (10 Years): 12

Top Topics

Unsupervised Learning

Posterior Probability

Tensor Decomposition

Generative Model

Top Venues

Nat. Mac. Intell.

J. Mach. Learn. Res.

Publications

Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven G. Gilmour, Stephen J. Roberts, Christopher C. Holmes
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. Nat. Mac. Intell. 6 (2) (2024)
Lucile Ter-Minassian, Oscar Clivio, Karla DiazOrdaz, Robin J. Evans, Christopher C. Holmes
PWSHAP: A Path-Wise Explanation Model for Targeted Variables. ICML (2023)
Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Christopher C. Holmes
Multi-Facet Clustering Variational Autoencoders. CoRR (2021)
Matthew Willetts, Alexander Camuto, Tom Rainforth, Stephen J. Roberts, Christopher C. Holmes
Improving VAEs' Robustness to Adversarial Attack. ICLR (2021)
Edwin Fong, Simon Lyddon, Christopher C. Holmes
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap. CoRR (2019)
Matthew Willetts, Stephen J. Roberts, Christopher C. Holmes
Semi-Unsupervised Learning with Deep Generative Models: Clustering and Classifying using Ultra-Sparse Labels. CoRR (2019)
Tammo Rukat, Christopher C. Holmes, Christopher Yau
Probabilistic Boolean Tensor Decomposition. ICML (2018)
Tammo Rukat, Christopher C. Holmes, Christopher Yau
TensOrMachine: Probabilistic Boolean Tensor Decomposition. CoRR (2018)
Simon Lyddon, Stephen Walker, Christopher C. Holmes
Nonparametric learning from Bayesian models with randomized objective functions. CoRR (2018)
Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes
On Markov chain Monte Carlo methods for tall data. J. Mach. Learn. Res. 18 (2017)
Tammo Rukat, Christopher C. Holmes, Michalis K. Titsias, Christopher Yau
Bayesian Boolean Matrix Factorisation. ICML (2017)
Tammo Rukat, Christopher C. Holmes, Michalis K. Titsias, Christopher Yau
Bayesian Boolean Matrix Factorisation. CoRR (2017)
Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes
Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach. ICML (2014)
Michalis K. Titsias, Christopher Yau, Christopher C. Holmes
Statistical Inference in Hidden Markov Models using $k$-segment Constraints. CoRR (2013)
Jeremie Becker, Christopher Yau, John M. Hancock, Christopher C. Holmes
NucleoFinder: a statistical approach for the detection of nucleosome positions. Bioinform. 29 (6) (2013)
Jean-Baptiste Cazier, Christopher C. Holmes, John Broxholme
GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples. Bioinform. 28 (22) (2012)
Ajay Jasra, Christopher C. Holmes
Stochastic boosting algorithms. Stat. Comput. 21 (3) (2011)
Taane G. Clark, Susana G. Campino, Elisa Anastasi, Sarah Auburn, Yik Y. Teo, Kerrin S. Small, Kirk A. Rockett, Dominic Kwiatkowski, Christopher C. Holmes
A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals. Bioinform. 26 (16) (2010)
Shahzia Anjum, Arnaud Doucet, Christopher C. Holmes
A boosting approach to structure learning of graphs with and without prior knowledge. Bioinform. 25 (22) (2009)
Alex Webb, John M. Hancock, Christopher C. Holmes
Phylogenetic inference under recombination using Bayesian stochastic topology selection. Bioinform. 25 (2) (2009)
Jochen W. Klingelhoefer, Loukas Moutsianas, Christopher C. Holmes
Approximate Bayesian feature selection on a large meta-dataset offers novel insights on factors that effect siRNA potency. Bioinform. 25 (13) (2009)
Ajay Jasra, Arnaud Doucet, David A. Stephens, Christopher C. Holmes
Interacting sequential Monte Carlo samplers for trans-dimensional simulation. Comput. Stat. Data Anal. 52 (4) (2008)
Eleni Giannoulatou, Christopher Yau, Stefano Colella, Jiannis Ragoussis, Christopher C. Holmes
GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population. Bioinform. 24 (19) (2008)
Ajay Jasra, David A. Stephens, Christopher C. Holmes
On population-based simulation for static inference. Stat. Comput. 17 (3) (2007)
Christopher C. Holmes, Dave Denison
Classification with Bayesian MARS. Mach. Learn. 50 (1-2) (2003)
Stephen J. Roberts, Christopher C. Holmes, Dave Denison
Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo. ICANN (2001)
Stephen J. Roberts, Christopher C. Holmes, Dave Denison
Minimum-Entropy Data Partitioning Using Reversible Jump Markov Chain Monte Carlo. IEEE Trans. Pattern Anal. Mach. Intell. 23 (8) (2001)
Christopher C. Holmes, Bani K. Mallick
Bayesian wavelet networks for nonparametric regression. IEEE Trans. Neural Networks Learn. Syst. 11 (1) (2000)