Deep Generative Missingness Pattern-Set Mixture Models. - Sahra Ghalebikesabi; Rob Cornish; Chris C. Holmes; Luke J. Kelly (AISTATS, 2021)

On Locality of Local Explanation Models. - Sahra Ghalebikesabi; Lucile Ter-Minassian; Karla DiazOrdaz; Chris C. Holmes (NeurIPS, 2021)

Deep Generative Pattern-Set Mixture Models for Nonignorable Missingness. - Sahra Ghalebikesabi; Rob Cornish; Luke J. Kelly; Chris C. Holmes (CoRR, 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)

Density Estimation with Autoregressive Bayesian Predictives. - Sahra Ghalebikesabi; Chris C. Holmes; Edwin Fong; Brieuc Lehmann (CoRR, 2022)

AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires. - Melanie F. Pradier; Niranjani Prasad; Paidamoyo Chapfuwa; Sahra Ghalebikesabi; Maximilian Ilse; Steven Woodhouse; Rebecca Elyanow; Javier Zazo; Javier González Hernández; Julia Greissl; Edward Meeds (MLHC, 2023)

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

A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. - Veit David Wild; Sahra Ghalebikesabi; Dino Sejdinovic; Jeremias Knoblauch (NeurIPS, 2023)

Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates. - Sahra Ghalebikesabi; Chris C. Holmes; Edwin Fong; Brieuc Lehmann (UAI, 2023)

Differentially Private Diffusion Models Generate Useful Synthetic Images. - Sahra Ghalebikesabi; Leonard Berrada; Sven Gowal; Ira Ktena; Robert Stanforth; Jamie Hayes; Soham De; Samuel L. Smith; Olivia Wiles; Borja Balle (CoRR, 2023)

AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires. - Melanie F. Pradier; Niranjani Prasad; Paidamoyo Chapfuwa; Sahra Ghalebikesabi; Max Ilse; Steven Woodhouse; Rebecca Elyanow; Javier Zazo; Javier González Hernández; Julia Greissl; Edward Meeds (CoRR, 2023)

AirGapAgent: Protecting Privacy-Conscious Conversational Agents. - Eugene Bagdasarian; Ren Yi; Sahra Ghalebikesabi; Peter Kairouz; Marco Gruteser; Sewoong Oh; Borja Balle; Daniel Ramage (CCS, 2024)

Explainable AI for survival analysis: a median-SHAP approach. - Lucile Ter-Minassian; Sahra Ghalebikesabi; Karla Diaz-Ordaz; Chris C. Holmes (CoRR, 2024)

Air Gap: Protecting Privacy-Conscious Conversational Agents. - Eugene Bagdasaryan; Ren Yi; Sahra Ghalebikesabi; Peter Kairouz; Marco Gruteser; Sewoong Oh; Borja Balle; Daniel Ramage (CoRR, 2024)

Operationalizing Contextual Integrity in Privacy-Conscious Assistants. - Sahra Ghalebikesabi; Eugene Bagdasaryan; Ren Yi; Itay Yona; Ilia Shumailov; Aneesh Pappu; Chongyang Shi 003; Laura Weidinger; Robert Stanforth; Leonard Berrada; Pushmeet Kohli; Po-Sen Huang; et al. (CoRR, 2024)

CI-Bench: Benchmarking Contextual Integrity of AI Assistants on Synthetic Data. - Zhao Cheng; Diane Wan; Matthew Abueg; Sahra Ghalebikesabi; Ren Yi; Eugene Bagdasarian; Borja Balle; Stefan Mellem; Shawn O'Banion (CoRR, 2024)

A framework for longitudinal latent factor modelling of treatment response in clinical trials with applications to Psoriatic Arthritis and Rheumatoid Arthritis. - Fabian Falck; Xuan Zhu; Sahra Ghalebikesabi; Matthias Kormaksson; Marc Vandemeulebroecke; Cong Zhang; Ruvie Martin; Stephen Gardiner; Chun Hei Kwok; Dominique M. West; Luis A. Santos; Chengeng Tian; et al. (J. Biomed. Informatics, 2024)

Privacy Awareness for Information-Sharing Assistants: A Case-study on Form-filling with Contextual Integrity. - Sahra Ghalebikesabi; Eugene Bagdasarian; Ren Yi; Itay Yona; Ilia Shumailov; Aneesh Pappu; Chongyang Shi 003; Laura Weidinger; Robert Stanforth; Leonard Berrada; Pushmeet Kohli; Po-Sen Huang; et al. (Trans. Mach. Learn. Res., 2025)

Strong Membership Inference Attacks on Massive Datasets and (Moderately) Large Language Models. - Jamie Hayes; Ilia Shumailov; Christopher A. Choquette-Choo; Matthew Jagielski; Georgios Kaissis; Katherine Lee; Milad Nasr; Sahra Ghalebikesabi; Niloofar Mireshghallah; Meenatchi Sundaram Mutu Selva Annamalai; Igor Shilov; Matthieu Meeus; et al. (CoRR, 2025)