1 citations · 1 across the 6 of their papers we have counts for
6 papers
Learning Causal Orderings for In-Context Tabular Prediction
Sascha Xu, Sarah Mameche, Jilles Vreeken
In-context learning for tabular data sets strong predictive standards in observational settings; it however primarily relies on correlational structure, which becomes unreliable un…
Differential Subgroup Discovery: Characterizing Where Two Populations Differ, and Why
Sascha Xu, Jilles Vreeken
We study the problem of understanding where two populations differ within a feature space, which we formalize in the concept of a differential subgroup: a subset of individuals fro…
Discovering Subgroups with Exceptional Survival Characteristics
Mhd Jawad Al Rahwanji, Sascha Xu, Nils Philipp Walter +1
In many applications, it is important to identify subpopulations that survive longer or shorter than the rest of the population. In medicine, for example, it allows determining whi…
Neuro-Symbolic Rule Lists
Sascha Xu, Nils Philipp Walter, Jilles Vreeken
Machine learning models deployed in sensitive areas such as healthcare must be interpretable to ensure accountability and fairness. Rule lists (if Age < 35 Priors > 0 then…
Learning Exceptional Subgroups by End-to-End Maximizing KL-divergence
Sascha Xu, Nils Philipp Walter, Janis Kalofolias +1
Finding and describing sub-populations that are exceptional regarding a target property has important applications in many scientific disciplines, from identifying disadvantaged de…
Succinct Interaction-Aware Explanations
Sascha Xu, Joscha Cüppers, Jilles Vreeken
SHAP is a popular approach to explain black-box models by revealing the importance of individual features. As it ignores feature interactions, SHAP explanations can be confusing up…