1 citations · 3 across the 21 of their papers we have counts for
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What Comes Next and Why: Interpretable Next-Event Prediction with Neuro-Symbolic Rules
Tim Nico Bauerschmidt, Isabel Valera, Jilles Vreeken
In real-world applications, being able to explain why a prediction is made is often as important - if not more so - than achieving high accuracy. However, existing methods for sequ…
Mapping and Advancing the Scalability-Accuracy Frontier of Nonlinear Causal Discovery
Hendrik Suhr, Sascha Xu, Jilles Vreeken
Scalable nonlinear causal discovery requires methods that combine flexible mechanism estimators with efficient search over large graph spaces. Several algorithmic families have bee…
In-Context Time Series Classification with Random Convolutional Features
Joscha Cüppers, Jilles Vreeken
Time series classification is central to domains such as medical signal analysis, industrial monitoring, and sensor-based activity recognition, where class information manifests as…
Identifying Structural Biases from Causal Mechanism Shifts
Praharsh Nanavati, Jilles Vreeken, David Kaltenpoth
Causal discovery methods commonly assume that all data is independently and identically distributed (i.i.d.) and that there are no unmeasured variables affecting the system. In pra…
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…
Root Cause Analysis of Measurement and Mechanistic Anomalies
Hendrik Suhr, David Kaltenpoth, Jilles Vreeken
Root cause analysis of anomalies aims to identify how and why a sample deviates from the normal process. Existing methods primarily focus on telling which features are responsible,…