13 citations · 24 across the 3 of their papers we have counts for
3 papers
Comparing Explanation Methods for Traditional Machine Learning Models Part 2: Quantifying Model Explainability Faithfulness and Improvements with Dimensionality Reduction
Montgomery Flora, Corey Potvin, Amy McGovern +1
Machine learning (ML) models are becoming increasingly common in the atmospheric science community with a wide range of applications. To enable users to understand what an ML model…
Comparing Explanation Methods for Traditional Machine Learning Models Part 1: An Overview of Current Methods and Quantifying Their Disagreement
Montgomery Flora, Corey Potvin, Amy McGovern +1
With increasing interest in explaining machine learning (ML) models, the first part of this two-part study synthesizes recent research on methods for explaining global and local as…
Possible Implications of a Vortex Gas Model and Self-Similarity for Tornadogenesis and Maintenance
Douglas P. Dokken, Kurt Scholz, Mikhail M. Shvartsman +4
We describe tornadogenesis and maintenance using the 3-dimensional vortex gas model presented in Chorin (1994) and developed further in Flandoli and Gubinelli (2002). We suggest th…