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stat.ML2026
A Regularization-Sharpness Tradeoff for Linear Interpolators
Qingyi Hu, Liam Hodgkinson
The rule of thumb regarding the relationship between the bias-variance tradeoff and model size plays a key role in classical machine learning, but is now well-known to break down i…
stat.ML2025
Uncertainty Quantification with the Empirical Neural Tangent Kernel
Joseph Wilson, Chris van der Heide, Liam Hodgkinson +1
While neural networks have demonstrated impressive performance across various tasks, accurately quantifying uncertainty in their predictions is essential to ensure their trustworth…