49 citations · 83 across the 16 of their papers we have counts for
5 papers · 1 filter
Differentially Private Statistical Inference through -Divergence One Posterior Sampling
Jack Jewson, Sahra Ghalebikesabi, Chris Holmes
Differential privacy guarantees allow the results of a statistical analysis involving sensitive data to be released without compromising the privacy of any individual taking part.…
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods
Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic +1
We establish the first mathematically rigorous link between Bayesian, variational Bayesian, and ensemble methods. A key step towards this it to reformulate the non-convex optimisat…
Quasi-Bayesian Nonparametric Density Estimation via Autoregressive Predictive Updates
Sahra Ghalebikesabi, Chris Holmes, Edwin Fong +1
Bayesian methods are a popular choice for statistical inference in small-data regimes due to the regularization effect induced by the prior. In the context of density estimation, t…
Mitigating Statistical Bias within Differentially Private Synthetic Data
Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson +3
Increasing interest in privacy-preserving machine learning has led to new and evolved approaches for generating private synthetic data from undisclosed real data. However, mechanis…
Deep Generative Pattern-Set Mixture Models for Nonignorable Missingness
Sahra Ghalebikesabi, Rob Cornish, Luke J. Kelly +1
We propose a variational autoencoder architecture to model both ignorable and nonignorable missing data using pattern-set mixtures as proposed by Little (1993). Our model explicitl…