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cs.LG2026

The Signal in the Noise: OOD Detection Through Goodness-of-Fit Testing in Factorised Latent Spaces

Philipp Bomatter, Jack Geary, Henry Gouk

Deep generative models offer a natural foundation for out-of-distribution (OOD) detection, yet prior work has shown that their assigned likelihoods are notoriously unreliable indic…

cs.LG2026

A Sobering Look at Tabular Data Generation via Probabilistic Circuits

Davide Scassola, Dylan Ponsford, Adrián Javaloy +5

Tabular data is more challenging to generate than text and images, due to its heterogeneous features and much lower sample sizes. On this task, diffusion-based models are the curre…

cs.LG2026

Magnitude Distance: A Geometric Measure of Dataset Similarity

Sahel Torkamani, Henry Gouk, Rik Sarkar

Quantifying the distance between datasets is a fundamental question in mathematics and machine learning. We propose \textit{magnitude distance}, a novel distance metric defined on…

cs.LG2025

Computing Strategic Responses to Non-Linear Classifiers

Jack Geary, Boyan Gao, Henry Gouk

We consider the problem of strategic classification, where the act of deploying a classifier leads to strategic behaviour that induces a distribution shift on subsequent observatio…

cs.LG2025

Model Diffusion for Certifiable Few-shot Transfer Learning

Fady Rezk, Royson Lee, Henry Gouk +2

In contemporary deep learning, a prevalent and effective workflow for solving low-data problems is adapting powerful pre-trained foundation models (FMs) to new tasks via parameter-…

cs.LG2025

Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning

Taehoon Kim, Henry Gouk, Minyoung Kim +1

Certifying the IID generalisation ability of deep networks is the first of many requirements for trusting AI in high-stakes applications from medicine to security. However, when in…