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Kristin Blesch

2 accepted papers

2025

Conditional Feature Importance with Generative Modeling Using Adversarial Random Forests

AAAI 2025technical

This paper proposes a method for measuring conditional feature importance via generative modeling. In explainable artificial intelligence (XAI), conditional feature importance assesses the impact of a feature on a prediction model's performance given the information of other features. Model-agnostic…

2023

Adversarial Random Forests for Density Estimation and Generative Modeling

AISTATS 2023poster

We propose methods for density estimation and data synthesis using a novel form of unsupervised random forests. Inspired by generative adversarial networks, we implement a recursive procedure in which trees gradually learn structural properties of the data through alternating rounds of generation an…