Bailey Andrew — accepted AI-conference papers

2025

Gaussian Graphical Modelling Without Independence Assumptions for Uncentered Data

Bailey Andrew, David R. Westhead, Luisa Cutillo

AAAI 2025technical

The independence assumption between random variables is a useful tool to increase the tractability of a modelling framework. However, this assumption can be too simplistic; failing to take dependencies into account can cause models to fail dramatically. The field of multi-axis graphical modelling…

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2025

The Strong Product Model for Network Inference without Independence Assumptions

Bailey Andrew, David Robert Westhead, Luisa Cutillo

AISTATS 2025poster

Multi-axis graphical modelling techniques allow us to perform network inference without making independence assumptions. This is done by replacing the independence assumption with a weaker assumption about the interaction between the axes; there are several choices for which assumption to use. In…

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