435 citations · 463 across the 29 of their papers we have counts for
32 papers
Generalization in Neural Networks Through the Lens of Magnitude Potential
Sahel Torkamani, Henry Gouk, Rik Sarkar
Explaining generalization and training dynamics in neural networks remains a challenge, and various approaches have been developed to study different aspects of these phenomena. In…
Non-Linear Strategic Classification Made Practical
Jack Geary, Boyan Gao, Henry Gouk
Algorithmic developments in Strategic Classification have been mostly limited to linear classifiers in settings where the best response has a closed-form solution or can be easily…
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…
A Sobering Look at Tabular Data Generation via Probabilistic Circuits
Davide Scassola, Dylan Ponsford, Adrián Javaloy +4
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…
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…
The Reward Model Selection Crisis in Personalized Alignment
Fady Rezk, Yuangang Pan, Chuan-Sheng Foo +4
Personalized alignment from preference data has focused primarily on improving personal reward model (RM) accuracy, with the implicit assumption that better preference ranking tran…