Sahra Ghalebikesabi

According to our database, Sahra Ghalebikesabi authored at least 18 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, Yu Pang, Aimee Readie, Gregory Ligozio, Kunal K. Gandhi, Thomas E. Nichols, Ann-Marie Mallon, Luke J. Kelly, David Ohlssen, George Nicholson

J. Biomed. Informatics, 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

Operationalizing Contextual Integrity in Privacy-Conscious Assistants.

Sahra Ghalebikesabi, Eugene Bagdasaryan, Ren Yi, Itay Yona, Ilia Shumailov, Aneesh Pappu, Chongyang Shi, Laura Weidinger, Robert Stanforth, Leonard Berrada, Pushmeet Kohli, Po-Sen Huang, Borja Balle

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

Explainable AI for survival analysis: a median-SHAP approach.

Lucile Ter-Minassian, Sahra Ghalebikesabi, Karla Diaz-Ordaz, Chris C. Holmes

CoRR, 2024

AirGapAgent: Protecting Privacy-Conscious Conversational Agents.

Eugene Bagdasarian, Ren Yi, Sahra Ghalebikesabi, Peter Kairouz, Marco Gruteser, Sewoong Oh, Borja Balle, Daniel Ramage

Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, 2024

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

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

Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates.

Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann

Proceedings of the Uncertainty in Artificial Intelligence, 2023

A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods.

Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Differentially Private Statistical Inference through β-Divergence One Posterior Sampling.

Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

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

Proceedings of the Machine Learning for Healthcare Conference, 2023

2022

Density Estimation with Autoregressive Bayesian Predictives.

Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann

CoRR, 2022

Mitigating statistical bias within differentially private synthetic data.

Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes

Proceedings of the Uncertainty in Artificial Intelligence, 2022

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

Deep Generative Pattern-Set Mixture Models for Nonignorable Missingness.

Sahra Ghalebikesabi, Rob Cornish, Luke J. Kelly, Chris C. Holmes

CoRR, 2021

On Locality of Local Explanation Models.

Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla DiazOrdaz, Chris C. Holmes

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Generative Missingness Pattern-Set Mixture Models.

Sahra Ghalebikesabi, Rob Cornish, Chris C. Holmes, Luke J. Kelly

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021