Christopher C. Holmes

According to our database, Christopher C. Holmes authored at least 78 papers between 1998 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Development and assessment of a machine learning tool for predicting emergency admission in Scotland.

James Liley, Gergo Bohner, Samuel R. Emerson, Bilal A. Mateen, Katie Borland, David Carr, Scott Heald, Samuel D. Oduro, Jill Ireland, Keith Moffat, Rachel Porteous, Stephen Riddell, Simon Rogers, Ioanna Thoma, Nathan Cunningham, Chris Holmes, Katrina Payne, Sebastian J. Vollmer, Catalina A. Vallejos, Louis J. M. Aslett

npj Digit. Medicine, 2024

Publisher Correction: Development and assessment of a machine learning tool for predicting emergency admission in Scotland.

James Liley, Gergo Bohner, Samuel R. Emerson, Bilal A. Mateen, Katie Borland, David Carr, Scott Heald, Samuel D. Oduro, Jill Ireland, Keith Moffat, Rachel Porteous, Stephen Riddell, Simon Rogers, Ioanna Thoma, Nathan Cunningham, Chris Holmes, Katrina Payne, Sebastian J. Vollmer, Catalina A. Vallejos, Louis J. M. Aslett

npj Digit. Medicine, 2024

Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers.

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

Nat. Mac. Intell., 2024

Towards Representation Learning for Weighting Problems in Design-Based Causal Inference.

Oscar Clivio, Avi Feller, Christopher C. Holmes

CoRR, 2024

Is merging worth it? Securely evaluating the information gain for causal dataset acquisition.

Jake Fawkes, Lucile Ter-Minassian, Desi Ivanova, Uri Shalit, Christopher C. Holmes

CoRR, 2024

On Subjective Uncertainty Quantification and Calibration in Natural Language Generation.

Ziyu Wang, Chris Holmes

CoRR, 2024

On Uncertainty Quantification for Near-Bayes Optimal Algorithms.

Ziyu Wang, Chris Holmes

CoRR, 2024

Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection.

Sam Dauncey, Chris C. Holmes, Christopher Williams, Fabian Falck

CoRR, 2024

Explainable AI for survival analysis: a median-SHAP approach.

Lucile Ter-Minassian, Sahra Ghalebikesabi, Karla Diaz-Ordaz, Chris C. Holmes

CoRR, 2024

Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation.

Lucile Ter-Minassian, Liran Szlak, Ehud Karavani, Chris C. Holmes, Yishai Shimoni

CoRR, 2024

Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective.

Fabian Falck, Ziyu Wang, Christopher C. Holmes

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Learning from data with structured missingness.

Robin Mitra, Sarah F. McGough, Tapabrata Chakraborti, Chris C. Holmes, Ryan Copping, Niels Hagenbuch, Stefanie Biedermann, Jack Noonan, Brieuc Lehmann, Aditi Shenvi, Xuan Vinh Doan, David Leslie, Ginestra Bianconi, Rubén J. Sánchez-García, Alisha Davies, Maxine Mackintosh, Eleni-Rosalina Andrinopoulou, Anahid Basiri, Chris Harbron, Ben D. MacArthur

Nat. Mac. Intell., January, 2023

Causal Falsification of Digital Twins.

Rob Cornish, Muhammad Faaiz Taufiq, Arnaud Doucet, Chris C. Holmes

CoRR, 2023

Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates.

Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann

Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Unified Framework for U-Net Design and Analysis.

Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Differentially Private Statistical Inference through β-Divergence One Posterior Sampling.

Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PWSHAP: A Path-Wise Explanation Model for Targeted Variables.

Lucile Ter-Minassian, Oscar Clivio, Karla DiazOrdaz, Robin J. Evans, Christopher C. Holmes

Proceedings of the International Conference on Machine Learning, 2023

2022

Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19.

Davide Pigoli, Kieran Baker, Jobie Budd, Lorraine Butler, Harry Coppock, Sabrina Egglestone, Steven G. Gilmour, Chris C. Holmes, David Hurley, Radka Jersakova, Ivan Kiskin, Vasiliki Koutra, Jonathon Mellor, George Nicholson, Joe Packham, Selina Patel, Richard Payne, Stephen J. Roberts, Björn W. Schuller, Ana Tendero Cañadas, Tracey Thornley, Alexander Titcomb

CoRR, 2022

Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers.

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 Gilmour, Stephen J. Roberts, Chris C. Holmes

CoRR, 2022

A large-scale and PCR-referenced vocal audio dataset for COVID-19.

Jobie Budd, Kieran Baker, Emma Karoune, Harry Coppock, Selina Patel, Ana Tendero Cañadas, Alexander Titcomb, Richard Payne, David Hurley, Sabrina Egglestone, Lorraine Butler, Jonathon Mellor, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Radka Jersakova, Rachel A. McKendry, Peter Diggle, Sylvia Richardson, Björn W. Schuller, Steven Gilmour, Davide Pigoli, Stephen J. Roberts, Josef Packham, Tracey Thornley, Chris C. Holmes

CoRR, 2022

Density Estimation with Autoregressive Bayesian Predictives.

Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann

CoRR, 2022

Mitigating statistical bias within differentially private synthetic data.

Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes

Proceedings of the Uncertainty in Artificial Intelligence, 2022

A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs.

Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Neural score matching for high-dimensional causal inference.

Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris C. Holmes

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale.

Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes

CoRR, 2021

Deep Generative Pattern-Set Mixture Models for Nonignorable Missingness.

Sahra Ghalebikesabi, Rob Cornish, Luke J. Kelly, Chris C. Holmes

CoRR, 2021

Neural Ensemble Search for Uncertainty Estimation and Dataset Shift.

Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Locality of Local Explanation Models.

Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla DiazOrdaz, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Conformal Bayesian Computation.

Edwin Fong, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Multi-Facet Clustering Variational Autoencoders.

Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections.

Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli

Proceedings of the 38th International Conference on Machine Learning, 2021

Improving VAEs' Robustness to Adversarial Attack.

Matthew Willetts, Alexander Camuto, Tom Rainforth, Stephen J. Roberts, Christopher C. Holmes

Proceedings of the 9th International Conference on Learning Representations, 2021

Foundations of Bayesian Learning from Synthetic Data.

Harrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris C. Holmes

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Deep Generative Missingness Pattern-Set Mixture Models.

Sahra Ghalebikesabi, Rob Cornish, Chris C. Holmes, Luke J. Kelly

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Towards a Theoretical Understanding of the Robustness of Variational Autoencoders.

Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

Learning Bijective Feature Maps for Linear ICA.

Alexander Camuto, Matthew Willetts, Chris C. Holmes, Brooks Paige, Stephen J. Roberts

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Improving the quality of machine learning in health applications and clinical research.

Bilal A. Mateen, James Liley, Alastair K. Denniston, Chris C. Holmes, Sebastian J. Vollmer

Nat. Mach. Intell., 2020

Relaxed-Responsibility Hierarchical Discrete VAEs.

Matthew Willetts, Xenia Miscouridou, Stephen J. Roberts, Chris C. Holmes

CoRR, 2020

Inferring proximity from Bluetooth Low Energy RSSI with Unscented Kalman Smoothers.

Tom Lovett, Mark Briers, Marcos Charalambides, Radka Jersakova, James Lomax, Chris C. Holmes

CoRR, 2020

Neural Ensemble Search for Performant and Calibrated Predictions.

Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh

CoRR, 2020

Risk scoring calculation for the current NHSx contact tracing app.

Mark Briers, Marcos Charalambides, Chris C. Holmes

CoRR, 2020

Explicit Regularisation in Gaussian Noise Injections.

Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels.

Matthew Willetts, Stephen J. Roberts, Chris C. Holmes

Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), 2020

2019

Regularising Deep Networks with DGMs.

Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes

CoRR, 2019

Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders.

Matthew Willetts, Stephen J. Roberts, Chris C. Holmes

CoRR, 2019

Disentangling Improves VAEs' Robustness to Adversarial Attacks.

Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes

CoRR, 2019

Semi-Unsupervised Learning with Deep Generative Models: Clustering and Classifying using Ultra-Sparse Labels.

Matthew Willetts, Stephen J. Roberts, Christopher C. Holmes

CoRR, 2019

Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap.

Edwin Fong, Simon Lyddon, Chris C. Holmes

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Principles of Bayesian Inference Using General Divergence Criteria.

Jack Jewson, Jim Q. Smith, Chris C. Holmes

Entropy, 2018

Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness.

Sebastian J. Vollmer, Bilal A. Mateen, Gergo Bohner, Franz J. Király, Rayid Ghani, Pall Jonsson, Sarah Cumbers, Adrian Jonas, Katherine S. L. McAllister, Puja Myles, David Granger, Mark Birse, Richard Branson, Karel G. M. Moons, Gary S. Collins, John P. A. Ioannidis, Chris C. Holmes, Harry Hemingway

CoRR, 2018

Semi-unsupervised Learning of Human Activity using Deep Generative Models.

Matthew Willetts, Aiden R. Doherty, Stephen J. Roberts, Chris C. Holmes

CoRR, 2018

TensOrMachine: Probabilistic Boolean Tensor Decomposition.

Tammo Rukat, Christopher C. Holmes, Christopher Yau

CoRR, 2018

Nonparametric learning from Bayesian models with randomized objective functions.

Simon Lyddon, Stephen Walker, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Probabilistic Boolean Tensor Decomposition.

Tammo Rukat, Christopher C. Holmes, Christopher Yau

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

On Markov chain Monte Carlo methods for tall data.

Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes

J. Mach. Learn. Res., 2017

Bayesian Boolean Matrix Factorisation.

Tammo Rukat, Christopher C. Holmes, Michalis K. Titsias, Christopher Yau

Proceedings of the 34th International Conference on Machine Learning, 2017

Encrypted Accelerated Least Squares Regression.

Pedro M. Esperança, Louis J. M. Aslett, Chris C. Holmes

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification.

Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, Lawrence Murray, Chris C. Holmes

Proceedings of the Genetic Programming Theory and Practice XIV, 2016

2015

Encrypted statistical machine learning: new privacy preserving methods.

Louis J. M. Aslett, Pedro M. Esperança, Chris C. Holmes

CoRR, 2015

A review of homomorphic encryption and software tools for encrypted statistical machine learning.

Louis J. M. Aslett, Pedro M. Esperança, Chris C. Holmes

CoRR, 2015

2014

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

Rémi Bardenet, Arnaud Doucet, Christopher C. Holmes

Proceedings of the 31th International Conference on Machine Learning, 2014

2013

Statistical Inference in Hidden Markov Models using $k$-segment Constraints.

Michalis K. Titsias, Christopher Yau, Christopher C. Holmes

CoRR, 2013

Integrative network-based Bayesian analysis of diverse genomics data.

Wenting Wang, Veerabhadran Baladandayuthapani, Chris C. Holmes, Kim-Anh Do

BMC Bioinform., 2013

NucleoFinder: a statistical approach for the detection of nucleosome positions.

Jérémie Becker, Christopher Yau, John M. Hancock, Christopher C. Holmes

Bioinform., 2013

2012

GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples.

Jean-Baptiste Cazier, Christopher C. Holmes, John Broxholme

Bioinform., 2012

2011

Stochastic boosting algorithms.

Ajay Jasra, Christopher C. Holmes

Stat. Comput., 2011

2010

A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals.

Taane G. Clark, Susana G. Campino, Elisa Anastasi, Sarah Auburn, Yik Y. Teo, Kerrin S. Small, Kirk A. Rockett, Dominic Kwiatkowski, Christopher C. Holmes

Bioinform., 2010

2009

Phylogenetic inference under recombination using Bayesian stochastic topology selection.

Alex Webb, John M. Hancock, Christopher C. Holmes

Bioinform., 2009

Approximate Bayesian feature selection on a large meta-dataset offers novel insights on factors that effect siRNA potency.

Jochen W. Klingelhoefer, Loukas Moutsianas, Christopher C. Holmes

Bioinform., 2009

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

Shahzia Anjum, Arnaud Doucet, Christopher C. Holmes

Bioinform., 2009

2008

Interacting sequential Monte Carlo samplers for trans-dimensional simulation.

Ajay Jasra, Arnaud Doucet, David A. Stephens, Christopher C. Holmes

Comput. Stat. Data Anal., 2008

GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population.

Eleni Giannoulatou, Christopher Yau, Stefano Colella, Jiannis Ragoussis, Christopher C. Holmes

Bioinform., 2008

2007

On population-based simulation for static inference.

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

Stat. Comput., 2007

2003

Classification with Bayesian MARS.

Christopher C. Holmes, Dave Denison

Mach. Learn., 2003

2001

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

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

IEEE Trans. Pattern Anal. Mach. Intell., 2001

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

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

Proceedings of the Artificial Neural Networks, 2001

2000

Bayesian wavelet networks for nonparametric regression.

Christopher C. Holmes, Bani K. Mallick

IEEE Trans. Neural Networks Learn. Syst., 2000

1998

Bayesian Radial Basis Functions of Variable Dimension.

Christopher C. Holmes, Bani K. Mallick

Neural Comput., 1998