# Exchangeable Gaussian Processes with application to epidemics

arXiv: https://arxiv.org/abs/2512.05227 · HTML: https://mlsanity.com/paper/2512.05227/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Dec 2025.

## Built on by (most cited first, 1 of 1)

- [Exchangeable Gaussian Processes for Staggered-Adoption Policy Evaluation](https://mlsanity.com/paper/2602.21031/) (2026)

## Abstract (arXiv)

We develop a Bayesian non-parametric framework based on multi-task Gaussian processes, appropriate for temporal shrinkage. We focus on a particular class of dynamic hierarchical models to obtain evidence-based knowledge of infectious disease burden. These models induce a parsimonious way to capture cross-dependence between groups while retaining a natural interpretation based on an underlying mean process, itself expressed as a Gaussian process. We analyse distinct types of outbreak data from recent epidemics and find that the proposed models result in improved predictive ability against competing alternatives.