1 citations · 1 across the 5 of their papers we have counts for
5 papers
Trustworthy Feature Importance Avoids Unrestricted Permutations
Emanuele Borgonovo, Francesco Cappelli, Xuefei Lu +2
Feature importance methods using unrestricted permutations are flawed due to extrapolation errors; such errors appear in all non-trivial variable importance approaches. We propose…
Doctor Rashomon and the UNIVERSE of Madness: Variable Importance with Unobserved Confounding and the Rashomon Effect
Jon Donnelly, Srikar Katta, Emanuele Borgonovo +1
Variable importance (VI) methods are often used for hypothesis generation, feature selection, and scientific validation. In the standard VI pipeline, an analyst estimates VI for a…
No for Some, Yes for Others: Persona Prompts and Other Sources of False Refusal in Language Models
Flor Miriam Plaza-del-Arco, Paul Röttger, Nino Scherrer +3
Large language models (LLMs) are increasingly integrated into our daily lives and personalized. However, LLM personalization might also increase unintended side effects. Recent wor…
gsaot: an R package for Optimal Transport-based sensitivity analysis
Leonardo Chiani, Emanuele Borgonovo, Elmar Plischke +1
gsaot is an R package for Optimal Transport-based global sensitivity analysis. It provides a simple interface for indices estimation using a variety of state-of-the-art Optimal Tra…
Neural Conditional Transport Maps
Carlos Rodriguez-Pardo, Leonardo Chiani, Emanuele Borgonovo +1
We present a neural framework for learning conditional optimal transport (OT) maps between probability distributions. Our approach introduces a conditioning mechanism capable of pr…