Chris C. Holmes

Publication Activity (10 Years)

Years Active: 2013-2024
Publications (10 Years): 54

Top Topics

Unsupervised Learning

Density Estimation

Top Venues

Publications

Sam Dauncey, Chris C. Holmes, Christopher Williams, Fabian Falck
Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection. CoRR (2024)
Lucile Ter-Minassian, Liran Szlak, Ehud Karavani, Chris C. Holmes, Yishai Shimoni
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation. CoRR (2024)
Lucile Ter-Minassian, Sahra Ghalebikesabi, Karla Diaz-Ordaz, Chris C. Holmes
Explainable AI for survival analysis: a median-SHAP approach. CoRR (2024)
Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes
Differentially Private Statistical Inference through β-Divergence One Posterior Sampling. NeurIPS (2023)
Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. CoRR (2023)
Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes
Differentially Private Statistical Inference through β-Divergence One Posterior Sampling. CoRR (2023)
Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed
A Unified Framework for U-Net Design and Analysis. NeurIPS (2023)
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 Sánchez-García, Alisha Davies, Maxine Mackintosh, Eleni-Rosalina Andrinopoulou, Anahid Basiri, Chris Harbron, Ben D. MacArthur
Learning from data with structured missingness. CoRR (2023)
Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann
Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates. UAI (2023)
Lucile Ter-Minassian, Oscar Clivio, Karla Diaz-Ordaz, Robin J. Evans, Chris C. Holmes
PWSHAP: A Path-Wise Explanation Model for Targeted Variables. CoRR (2023)
Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed
A Unified Framework for U-Net Design and Analysis. CoRR (2023)
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
Learning from data with structured missingness. Nat. Mac. Intell. 5 (1) (2023)
Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann
Density Estimation with Autoregressive Bayesian Predictives. CoRR (2022)
Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris C. Holmes
Neural score matching for high-dimensional causal inference. AISTATS (2022)
Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts
A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. NeurIPS (2022)
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
A large-scale and PCR-referenced vocal audio dataset for COVID-19. CoRR (2022)
Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes
Mitigating statistical bias within differentially private synthetic data. UAI (2022)
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
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. CoRR (2022)
Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris C. Holmes
Neural Score Matching for High-Dimensional Causal Inference. CoRR (2022)
Edwin Fong, Chris C. Holmes
Conformal Bayesian Computation. NeurIPS (2021)
Alexander Camuto, Matthew Willetts, Chris C. Holmes, Brooks Paige, Stephen J. Roberts
Learning Bijective Feature Maps for Linear ICA. AISTATS (2021)
Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh
Neural Ensemble Search for Uncertainty Estimation and Dataset Shift. NeurIPS (2021)
Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla Diaz-Ordaz, Chris C. Holmes
On Locality of Local Explanation Models. CoRR (2021)
Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. CoRR (2021)
Sahra Ghalebikesabi, Rob Cornish, Luke J. Kelly, Chris C. Holmes
Deep Generative Pattern-Set Mixture Models for Nonignorable Missingness. CoRR (2021)
Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla DiazOrdaz, Chris C. Holmes
On Locality of Local Explanation Models. NeurIPS (2021)
Sahra Ghalebikesabi, Rob Cornish, Chris C. Holmes, Luke J. Kelly
Deep Generative Missingness Pattern-Set Mixture Models. AISTATS (2021)
Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Chris C. Holmes
Multi-Facet Clustering Variational Autoencoders. NeurIPS (2021)
Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. ICML (2021)
Harrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris C. Holmes
Foundations of Bayesian Learning from Synthetic Data. AISTATS (2021)
Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes
Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale. CoRR (2021)
Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. AISTATS (2021)
Matthew Willetts, Stephen J. Roberts, Chris C. Holmes
Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels. IEEE BigData (2020)
Harrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris C. Holmes
Foundations of Bayesian Learning from Synthetic Data. CoRR (2020)
Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes
Explicit Regularisation in Gaussian Noise Injections. NeurIPS (2020)
Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. CoRR (2020)
Bilal A. Mateen, James Liley, Alastair K. Denniston, Chris C. Holmes, Sebastian J. Vollmer
Improving the quality of machine learning in health applications and clinical research. Nat. Mach. Intell. 2 (10) (2020)
Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes
Explicit Regularisation in Gaussian Noise Injections. CoRR (2020)
Mark Briers, Marcos Charalambides, Chris C. Holmes
Risk scoring calculation for the current NHSx contact tracing app. CoRR (2020)
Tom Lovett, Mark Briers, Marcos Charalambides, Radka Jersakova, James Lomax, Chris C. Holmes
Inferring proximity from Bluetooth Low Energy RSSI with Unscented Kalman Smoothers. CoRR (2020)
Alexander Camuto, Matthew Willetts, Brooks Paige, Chris C. Holmes, Stephen J. Roberts
Learning Bijective Feature Maps for Linear ICA. CoRR (2020)
Matthew Willetts, Xenia Miscouridou, Stephen J. Roberts, Chris C. Holmes
Relaxed-Responsibility Hierarchical Discrete VAEs. CoRR (2020)
Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh
Neural Ensemble Search for Performant and Calibrated Predictions. CoRR (2020)
Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes
Regularising Deep Networks with DGMs. CoRR (2019)
Edwin Fong, Simon Lyddon, Chris C. Holmes
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap. ICML (2019)
Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes
Disentangling Improves VAEs' Robustness to Adversarial Attacks. CoRR (2019)
Matthew Willetts, Stephen J. Roberts, Chris C. Holmes
Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders. CoRR (2019)
Matthew Willetts, Aiden Doherty, Stephen J. Roberts, Chris C. Holmes
Semi-unsupervised Learning of Human Activity using Deep Generative Models. CoRR (2018)
Jack Jewson, Jim Q. Smith, Chris C. Holmes
Principles of Bayesian Inference Using General Divergence Criteria. Entropy 20 (6) (2018)
Simon Lyddon, Stephen Walker, Chris C. Holmes
Nonparametric learning from Bayesian models with randomized objective functions. NeurIPS (2018)
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
Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness. CoRR (2018)
Pedro M. Esperança, Louis J. M. Aslett, Chris C. Holmes
Encrypted Accelerated Least Squares Regression. AISTATS (2017)
Pedro M. Esperança, Louis J. M. Aslett, Chris C. Holmes
Encrypted accelerated least squares regression. CoRR (2017)
Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, Lawrence Murray, Chris C. Holmes
PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification. GPTP (2016)
Louis J. M. Aslett, Pedro M. Esperança, Chris C. Holmes
Encrypted statistical machine learning: new privacy preserving methods. CoRR (2015)
Louis J. M. Aslett, Pedro M. Esperança, Chris C. Holmes
A review of homomorphic encryption and software tools for encrypted statistical machine learning. CoRR (2015)
Wenting Wang, Veerabhadran Baladandayuthapani, Chris C. Holmes, Kim-Anh Do
Integrative network-based Bayesian analysis of diverse genomics data. BMC Bioinform. 14 (S-13) (2013)