26 citations · 26 across the 4 of their papers we have counts for
4 papers
Model-agnostic variable importance for predictive uncertainty: an entropy-based approach
Danny Wood, Theodore Papamarkou, Matt Benatan +1
In order to trust the predictions of a machine learning algorithm, it is necessary to understand the factors that contribute to those predictions. In the case of probabilistic and…
A max-affine spline approximation of neural networks using the Legendre transform of a convex-concave representation
Adam Perrett, Danny Wood, Gavin Brown
This work presents a novel algorithm for transforming a neural network into a spline representation. Unlike previous work that required convex and piecewise-affine network operator…
A Unified Theory of Diversity in Ensemble Learning
Danny Wood, Tingting Mu, Andrew Webb +3
We present a theory of ensemble diversity, explaining the nature of diversity for a wide range of supervised learning scenarios. This challenge has been referred to as the holy gra…
Bias-Variance Decompositions for Margin Losses
Danny Wood, Tingting Mu, Gavin Brown
We introduce a novel bias-variance decomposition for a range of strictly convex margin losses, including the logistic loss (minimized by the classic LogitBoost algorithm), as well…