Chris C. Holmes

61 papers A* 11A 9Journal 39Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	A Real-World Evaluation of LLM Medication Safety Reviews in NHS Primary Care. CoRR Oliver Normand, Esther Borsi, Mitch Fruin, Lauren E. Walker, Jamie Heagerty, Chris C. Holmes, Anthony J. Avery, Iain E. Buchan, Harry Coppock
2024	J	`jnl`	Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection. CoRR Sam Dauncey, Chris C. Holmes, Christopher Williams, Fabian Falck
2024	J	`jnl`	Explainable AI for survival analysis: a median-SHAP approach. CoRR Lucile Ter-Minassian, Sahra Ghalebikesabi, Karla Diaz-Ordaz, Chris C. Holmes
2024	J	`jnl`	Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation. CoRR Lucile Ter-Minassian, Liran Szlak, Ehud Karavani, Chris C. Holmes, Yishai Shimoni
2024	A	`conf`	Towards Representation Learning for Weighting Problems in Design-Based Causal Inference. UAI Oscar Clivio, Avi Feller, Chris C. Holmes
2023	J	`jnl`	A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. CoRR Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts
2023	A*	`conf`	A Unified Framework for U-Net Design and Analysis. NeurIPS Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed
2023	J	`jnl`	A Unified Framework for U-Net Design and Analysis. CoRR Christopher Williams, Fabian Falck, George Deligiannidis, Chris C. Holmes, Arnaud Doucet, Saifuddin Syed
2023	J	`jnl`	Causal Falsification of Digital Twins. CoRR Rob Cornish, Muhammad Faaiz Taufiq, Arnaud Doucet, Chris C. Holmes
2023	A*	`conf`	Differentially Private Statistical Inference through β-Divergence One Posterior Sampling. NeurIPS Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes
2023	J	`jnl`	Differentially Private Statistical Inference through β-Divergence One Posterior Sampling. CoRR Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes
2023	J	`jnl`	Learning from data with structured missingness. CoRR 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 R. Davies, Maxine Mackintosh, Eleni-Rosalina Andrinopoulou, Anahid Basiri, Chris Harbron, Ben D. MacArthur
2023	J	`jnl`	Learning from data with structured missingness. Nat. Mac. Intell. 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 R. Davies, Maxine Mackintosh, Eleni-Rosalina Andrinopoulou, Anahid Basiri, Chris Harbron, Ben D. MacArthur
2023	J	`jnl`	PWSHAP: A Path-Wise Explanation Model for Targeted Variables. CoRR Lucile Ter-Minassian, Oscar Clivio, Karla Diaz-Ordaz, Robin J. Evans, Chris C. Holmes
2023	A	`conf`	Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates. UAI Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann
2022	A*	`conf`	A Multi-Resolution Framework for U-Nets with Applications to Hierarchical VAEs. NeurIPS Fabian Falck, Christopher Williams, Dominic Danks, George Deligiannidis, Christopher Yau, Chris C. Holmes, Arnaud Doucet, Matthew Willetts
2022	J	`jnl`	A large-scale and PCR-referenced vocal audio dataset for COVID-19. CoRR 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
2022	J	`jnl`	Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. CoRR 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
2022	J	`jnl`	Density Estimation with Autoregressive Bayesian Predictives. CoRR Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann
2022	A	`conf`	Mitigating statistical bias within differentially private synthetic data. UAI Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes
2022	J	`jnl`	Neural Score Matching for High-Dimensional Causal Inference. CoRR Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris C. Holmes
2022	A	`conf`	Neural score matching for high-dimensional causal inference. AISTATS Oscar Clivio, Fabian Falck, Brieuc Lehmann, George Deligiannidis, Chris C. Holmes
2022	J	`jnl`	Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19. CoRR 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
2021	A*	`conf`	Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. ICML Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
2021	J	`jnl`	Asymmetric Heavy Tails and Implicit Bias in Gaussian Noise Injections. CoRR Alexander Camuto, Xiaoyu Wang, Lingjiong Zhu, Chris C. Holmes, Mert Gürbüzbalaban, Umut Simsekli
2021	J	`jnl`	Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale. CoRR Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes
2021	A*	`conf`	Conformal Bayesian Computation. NeurIPS Edwin Fong, Chris C. Holmes
2021	A	`conf`	Deep Generative Missingness Pattern-Set Mixture Models. AISTATS Sahra Ghalebikesabi, Rob Cornish, Chris C. Holmes, Luke J. Kelly
2021	J	`jnl`	Deep Generative Pattern-Set Mixture Models for Nonignorable Missingness. CoRR Sahra Ghalebikesabi, Rob Cornish, Luke J. Kelly, Chris C. Holmes
2021	A	`conf`	Foundations of Bayesian Learning from Synthetic Data. AISTATS Harrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris C. Holmes
2021	A	`conf`	Learning Bijective Feature Maps for Linear ICA. AISTATS Alexander Camuto, Matthew Willetts, Chris C. Holmes, Brooks Paige, Stephen J. Roberts
2021	A*	`conf`	Multi-Facet Clustering Variational Autoencoders. NeurIPS Fabian Falck, Haoting Zhang, Matthew Willetts, George Nicholson, Christopher Yau, Chris C. Holmes
2021	A*	`conf`	Neural Ensemble Search for Uncertainty Estimation and Dataset Shift. NeurIPS Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh
2021	A*	`conf`	On Locality of Local Explanation Models. NeurIPS Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla DiazOrdaz, Chris C. Holmes
2021	J	`jnl`	On Locality of Local Explanation Models. CoRR Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla Diaz-Ordaz, Chris C. Holmes
2021	A	`conf`	Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. AISTATS Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth
2020	A*	`conf`	Explicit Regularisation in Gaussian Noise Injections. NeurIPS Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes
2020	J	`jnl`	Explicit Regularisation in Gaussian Noise Injections. CoRR Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes
2020	J	`jnl`	Foundations of Bayesian Learning from Synthetic Data. CoRR Harrison Wilde, Jack Jewson, Sebastian J. Vollmer, Chris C. Holmes
2020	J	`jnl`	Improving the quality of machine learning in health applications and clinical research. Nat. Mach. Intell. Bilal A. Mateen, James Liley, Alastair K. Denniston, Chris C. Holmes, Sebastian J. Vollmer
2020	J	`jnl`	Inferring proximity from Bluetooth Low Energy RSSI with Unscented Kalman Smoothers. CoRR Tom Lovett, Mark Briers, Marcos Charalambides, Radka Jersakova, James Lomax, Chris C. Holmes
2020	J	`jnl`	Learning Bijective Feature Maps for Linear ICA. CoRR Alexander Camuto, Matthew Willetts, Brooks Paige, Chris C. Holmes, Stephen J. Roberts
2020	J	`jnl`	Neural Ensemble Search for Performant and Calibrated Predictions. CoRR Sheheryar Zaidi, Arber Zela, Thomas Elsken, Chris C. Holmes, Frank Hutter, Yee Whye Teh
2020	J	`jnl`	Relaxed-Responsibility Hierarchical Discrete VAEs. CoRR Matthew Willetts, Xenia Miscouridou, Stephen J. Roberts, Chris C. Holmes
2020	J	`jnl`	Risk scoring calculation for the current NHSx contact tracing app. CoRR Mark Briers, Marcos Charalambides, Chris C. Holmes
2020	—	`conf`	Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels. IEEE BigData Matthew Willetts, Stephen J. Roberts, Chris C. Holmes
2020	J	`jnl`	Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. CoRR Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth
2019	J	`jnl`	Disentangling Improves VAEs' Robustness to Adversarial Attacks. CoRR Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes
2019	J	`jnl`	Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders. CoRR Matthew Willetts, Stephen J. Roberts, Chris C. Holmes
2019	J	`jnl`	Regularising Deep Networks with DGMs. CoRR Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes
2019	A*	`conf`	Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap. ICML Edwin Fong, Simon Lyddon, Chris C. Holmes
2018	J	`jnl`	Machine learning and AI research for Patient Benefit: 20 Critical Questions on Transparency, Replicability, Ethics and Effectiveness. CoRR 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
2018	A*	`conf`	Nonparametric learning from Bayesian models with randomized objective functions. NeurIPS Simon Lyddon, Stephen Walker, Chris C. Holmes
2018	J	`jnl`	Principles of Bayesian Inference Using General Divergence Criteria. Entropy Jack Jewson, Jim Q. Smith, Chris C. Holmes
2018	J	`jnl`	Semi-unsupervised Learning of Human Activity using Deep Generative Models. CoRR Matthew Willetts, Aiden R. Doherty, Stephen J. Roberts, Chris C. Holmes
2017	A	`conf`	Encrypted Accelerated Least Squares Regression. AISTATS Pedro M. Esperança, Louis J. M. Aslett, Chris C. Holmes
2017	J	`jnl`	Encrypted accelerated least squares regression. CoRR Pedro M. Esperança, Louis J. M. Aslett, Chris C. Holmes
2016	—	`conf`	PRETSL: Distributed Probabilistic Rule Evolution for Time-Series Classification. GPTP Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen, Lawrence Murray, Chris C. Holmes
2015	J	`jnl`	A review of homomorphic encryption and software tools for encrypted statistical machine learning. CoRR Louis J. M. Aslett, Pedro M. Esperança, Chris C. Holmes
2015	J	`jnl`	Encrypted statistical machine learning: new privacy preserving methods. CoRR Louis J. M. Aslett, Pedro M. Esperança, Chris C. Holmes
2013	J	`jnl`	Integrative network-based Bayesian analysis of diverse genomics data. BMC Bioinform. Wenting Wang, Veerabhadran Baladandayuthapani, Chris C. Holmes, Kim-Anh Do