Multi-core BUGS for fast Bayesian inference of large hierarchical models
Bayesian Meta-Learning for Improving Generalizability of Health Prediction Models With Similar Causal Mechanisms
Research Module in Econometrics and Statistics at Univ. Bonn (2019/2020) on Bayesian Hierarchical Models.
sparsely-encoded poisson matrix factorization
D'Agostini et al. (2026+) "A Bayesian Spatially Varying Coefficient Model for Surface Urban Heat Island Estimation"
Code and data companion for CBB 2024 Paper: Creating Something Different: Similarity, Contrast, and Representativeness in Categorization
Includes the R code and the supporting materials for our paper "Using machine learning to identify nontraditional spatial dependence in occupancy data"
OpenBUGS code and R functions to implement Bayesian hierarchical models for leveraging animal data in phase I oncology trials.
Modelled the effect of altitude on PM2.5 across Lombardy, Italy (2016-2021), using a Bayesian hierarchical spatio-temporal model fit via R-INLA/inlabru, isolating the altitude effect from residual spatial and seasonal variation. Collaborative project with Jackson Cramer and Zac Gavin for Bayesian Data Analysis (MATH11175) at UoE. Awarded 97.75%.
R package for Multi-Subject Multiscale Analysis of fMRI Data, or Other Multiscale Data
This project focuses on modelling the attacking and defensive strength of teams in the Portuguese First League of Football, along with the impact of home advantage.
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