| 2025 | AISTATS | Is Merging Worth It? Securely Evaluating the Information Gain for Causal Dataset Acquisition. | Jake Fawkes, Lucile Ter-Minassian, Desi R. Ivanova, Uri Shalit, Christopher C. Holmes |
| 2025 | AISTATS | Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation. | Lucile Ter-Minassian, Liran Szlak, Ehud Karavani, Christopher C. Holmes, Yishai Shimoni |
| 2025 | AISTATS | On Subjective Uncertainty Quantification and Calibration in Natural Language Generation. | Ziyu Wang, Christopher C. Holmes |
| 2024 | ICML | Is In-Context Learning in Large Language Models Bayesian? A Martingale Perspective. | Fabian Falck, Ziyu Wang, Christopher C. Holmes |
| 2023 | ICML | PWSHAP: A Path-Wise Explanation Model for Targeted Variables. | Lucile Ter-Minassian, Oscar Clivio, Karla DiazOrdaz, Robin J. Evans, Christopher C. Holmes |
| 2021 | ICLR | Improving VAEs' Robustness to Adversarial Attack. | Matthew Willetts, Alexander Camuto, Tom Rainforth, Stephen J. Roberts, Christopher C. Holmes |
| 2018 | ICML | Probabilistic Boolean Tensor Decomposition. | Tammo Rukat, Christopher C. Holmes, Christopher Yau |
| 2017 | ICML | Bayesian Boolean Matrix Factorisation. | Tammo Rukat, Christopher C. Holmes, Michalis K. Titsias, Christopher Yau |
| 2014 | ICML | Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach. | Rmi Bardenet, Arnaud Doucet, Christopher C. Holmes |
| 2001 | ICANN | Minimum-Entropy Data Clustering Using Reversible Jump Markov Chain Monte Carlo. | Stephen J. Roberts, Christopher C. Holmes, Dave Denison |