Policy making using computer simulators for complex physical systems : Bayesian decision support for the development of adaptive strategies. - Daniel B. Williamson (2010)

Evolving Bayesian Emulators for Structured Chaotic Time Series, with Application to Large Climate Models. - Daniel B. Williamson; Adam T. Blaker (SIAM/ASA J. Uncertain. Quantification, 2014)

Diagnostics-Driven Nonstationary Emulators Using Kernel Mixtures. - Victoria Volodina; Daniel B. Williamson (SIAM/ASA J. Uncertain. Quantification, 2020)

Cross-Validation-based Adaptive Sampling for Gaussian Process Models. - Hossein Mohammadi; Peter G. Challenor; Daniel B. Williamson; Marc Goodfellow (SIAM/ASA J. Uncertain. Quantification, 2022)

Quantifying Spatio-Temporal Boundary Condition Uncertainty for the North American Deglaciation. - James M. Salter; Daniel B. Williamson; Lauren J. Gregoire; Tamsin L. Edwards (SIAM/ASA J. Uncertain. Quantification, 2022)

Linked Deep Gaussian Process Emulation for Model Networks. - Deyu Ming; Daniel B. Williamson (CoRR, 2023)

On the meaning of uncertainty for ethical AI: philosophy and practice. - Cassandra Bird; Daniel B. Williamson; Sabina Leonelli (CoRR, 2023)

Deep Gaussian Process Emulation using Stochastic Imputation. - Deyu Ming; Daniel B. Williamson; Serge Guillas (Technometrics, 2023)

Feature Calibration for Computer Models. - Wenzhe Xu; Daniel B. Williamson; Frederic Hourdin; Romain Roehrig (SIAM/ASA J. Uncertain. Quantification, 2025)