11 papers
Private Generative Bootstrap via Blocking
Jinwon Sohn, Veronika Ročková
With AI systems gaining more access to individuals' information, it is important to protect privacy when reporting statistical answers. Equally important is to privatize the report…
Jigsaw Regularization in Whole-Slide Image Classification
So Won Jeong, Veronika Ročková
Computational pathology involves the digitization of stained tissues into whole-slide images (WSIs) that contain billions of pixels arranged as contiguous patches. Statistical anal…
Generative Bayesian Filtering and Parameter Learning
Edoardo Marcelli, Sean O'Hagan, Veronika Rockova
Generative Bayesian Filtering (GBF) provides a powerful and flexible framework for performing posterior inference in complex nonlinear and non-Gaussian state-space models. Our appr…
Conditional Flow Matching for Bayesian Posterior Inference
Percy S. Zhai, So Won Jeong, Veronika Ročková
We propose a generative multivariate posterior sampler via flow matching. It offers a simple training objective, and does not require access to likelihood evaluation. The method le…
From Small to Large Language Models: Revisiting the Federalist Papers
So Won Jeong, Veronika Ročková
For a long time, the authorship of the Federalist Papers had been a subject of inquiry and debate, not only by linguists and historians but also by statisticians. In what was argua…
AI-Powered Bayesian Inference
Sean O'Hagan, Veronika Ročková
The advent of Generative Artificial Intelligence (GAI) has heralded an inflection point that changed how society thinks about knowledge acquisition. While GAI cannot be fully trust…