Differentially Private Hamiltonian Monte Carlo. - Ossi Räisä; Antti Koskela; Antti Honkela (CoRR, 2021)

Noise-Aware Statistical Inference with Differentially Private Synthetic Data. - Ossi Räisä; Joonas Jälkö; Samuel Kaski; Antti Honkela (AISTATS, 2023)

Subsampling is not Magic: Why Large Batch Sizes Work for Differentially Private Stochastic Optimisation. - Ossi Räisä; Joonas Jälkö; Antti Honkela (ICML, 2024)

Noise-Aware Differentially Private Regression via Meta-Learning. - Ossi Räisä; Stratis Markou; Matthew Ashman; Wessel P. Bruinsma; Marlon Tobaben; Antti Honkela; Richard E. Turner (NeurIPS, 2024)

A Bias-Variance Decomposition for Ensembles over Multiple Synthetic Datasets. - Ossi Räisä; Antti Honkela (AISTATS, 2025)

Position: All Current Generative Fidelity and Diversity Metrics are Flawed. - Ossi Räisä; Boris van Breugel; Mihaela van der Schaar (CoRR, 2025)