no code implementations • 4 Apr 2024 • Susanne Dandl, Kristin Blesch, Timo Freiesleben, Gunnar König, Jan Kapar, Bernd Bischl, Marvin Wright
Counterfactual explanations elucidate algorithmic decisions by pointing to scenarios that would have led to an alternative, desired outcome.
1 code implementation • 13 Nov 2023 • Kristin Blesch, Marvin N. Wright
This paper introduces $\textit{arfpy}$, a python implementation of Adversarial Random Forests (ARF) (Watson et al., 2023), which is a lightweight procedure for synthesizing new data that resembles some given data.
1 code implementation • 6 Oct 2022 • Kristin Blesch, David S. Watson, Marvin N. Wright
The CPI enables conditional FI measurement that controls for any feature dependencies by sampling valid knockoffs - hence, generating synthetic data with similar statistical properties - for the data to be analyzed.
1 code implementation • 19 May 2022 • David S. Watson, Kristin Blesch, Jan Kapar, Marvin N. Wright
We propose methods for density estimation and data synthesis using a novel form of unsupervised random forests.