2 citations · 2 across the 5 of their papers we have counts for
6 papers
A Framework for Teaching the Responsible and Effective Use of Generative AI in Statistics and Data Science
Vinny Davies, Craig Alexander, Jennifer Gaskell +2
The rapid rise of generative artificial intelligence (AI) following the public release of tools such as ChatGPT has begun to reshape how students engage with coding, statistical an…
Spatial prediction of environmental processes using random forests: How best to account for spatial dependence?
Duncan Lee, Vinny Davies, Helen R. Savage +3
Geostatistical spatial prediction for environmental processes is typically undertaken using Gaussian process models via Kriging, while machine learning (ML) algorithms are state-of…
Reflections on the Future of Statistics Education in a Technological Era
Craig Alexander, Jennifer Gaskell, Vinny Davies
Keeping pace with rapidly evolving technology is a key challenge in teaching statistics. To equip students with essential skills for the modern workplace, educators must integrate…
A spatial random forest algorithm for population-level epidemiological risk assessment
Duncan Lee, Vinny Davies
Spatial epidemiology identifies the drivers of elevated population-level disease risks, using disease counts, exposures and known confounders at the areal unit level. Poisson regre…
Conditional autoregressive models fused with random forests to improve small-area spatial prediction
Cara MacBride, Vinny Davies, Duncan Lee
In areal unit data with missing or suppressed data, it desirable to create models that are able to predict observations that are not available. Traditional statistical methods achi…
Generalised linear models for prognosis and intervention: Theory, practice, and implications for machine learning
Kellyn F. Arnold, Vinny Davies, Marc de Kamps +3
Prediction and causal explanation are fundamentally distinct tasks of data analysis. In health applications, this difference can be understood in terms of the difference between pr…