32 citations · 52 across the 20 of their papers we have counts for
3 papers · 2 filters
Why Heavy-Tailed Weight Spectra Predict Model Quality
Joseph Wilson, Chris van der Heide, Liam Hodgkinson +3
A solid understanding of the predictive success of deep neural networks (DNNs) remains elusive. For example, while many data-dependent metrics exist that seek to predict model qual…
Is the Last Layer Sufficient for Uncertainty Quantification?
Joseph Wilson, Chris van der Heide, Liam Hodgkinson +1
Epistemic uncertainty quantification (UQ) for deep neural networks (DNNs) is a requirement for safe adoption of AI in mission-critical settings. Several leading methods for UQ line…
Free Decompression with Algebraic Spectral Curves
Siavash Ameli, Chris van der Heide, Liam Hodgkinson +1
Tools from random matrix theory have become central to deep learning theory, using spectral information to provide mechanisms for modeling generalization, robustness, scaling, and…