Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with beta-Divergences. - Jeremias Knoblauch; Jack Jewson; Theodoros Damoulas (NeurIPS, 2018)

Doubly Robust Bayesian Inference for Non-Stationary Streaming Data with β-Divergences. - Jeremias Knoblauch; Jack Jewson; Theodoros Damoulas (CoRR, 2018)

Principles of Bayesian Inference Using General Divergence Criteria. - Jack Jewson; Jim Q. Smith; Chris C. Holmes (Entropy, 2018)

A comment on the Duckworth-Lewis-Stern method. - Jack Jewson; Simon French 001 (J. Oper. Res. Soc., 2018)

Generalized Variational Inference. - Jeremias Knoblauch; Jack Jewson; Theodoros Damoulas (CoRR, 2019)

Foundations of Bayesian Learning from Synthetic Data. - Harrison Wilde; Jack Jewson; Sebastian J. Vollmer; Chris C. Holmes (AISTATS, 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)

Mitigating statistical bias within differentially private synthetic data. - Sahra Ghalebikesabi; Harry Wilde; Jack Jewson; Arnaud Doucet; Sebastian J. Vollmer; Chris C. Holmes (UAI, 2022)

An Optimization-centric View on Bayes' Rule: Reviewing and Generalizing Variational Inference. - Jeremias Knoblauch; Jack Jewson; Theodoros Damoulas (J. Mach. Learn. Res., 2022)

Differentially Private Statistical Inference through β-Divergence One Posterior Sampling. - Jack Jewson; Sahra Ghalebikesabi; Chris C. Holmes (NeurIPS, 2023)