5 citations · 11 across the 5 of their papers we have counts for
6 papers
Causal discovery with endogenous context variables
Wiebke Günther, Oana-Iuliana Popescu, Martin Rabel +3
Causal systems often exhibit variations of the underlying causal mechanisms between the variables of the system. Often, these changes are driven by different environments or intern…
AI for Extreme Event Modeling and Understanding: Methodologies and Challenges
Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs +22
In recent years, artificial intelligence (AI) has deeply impacted various fields, including Earth system sciences. Here, AI improved weather forecasting, model emulation, parameter…
Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation
Oana-Iuliana Popescu, Andreas Gerhardus, Jakob Runge
Conditional independence testing (CIT) is a common task in machine learning, e.g., for variable selection, and a main component of constraint-based causal discovery. While most cur…
Automated multilingual detection of Pro-Kremlin propaganda in newspapers and Telegram posts
Veronika Solopova, Oana-Iuliana Popescu, Christoph Benzmüller +1
The full-scale conflict between the Russian Federation and Ukraine generated an unprecedented amount of news articles and social media data reflecting opposing ideologies and narra…
Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset
Leon Sixt, Martin Schuessler, Oana-Iuliana Popescu +2
A variety of methods exist to explain image classification models. However, whether they provide any benefit to users over simply comparing various inputs and the model's respectiv…
Counterfactual Generation with Knockoffs
Oana-Iuliana Popescu, Maha Shadaydeh, Joachim Denzler
Human interpretability of deep neural networks' decisions is crucial, especially in domains where these directly affect human lives. Counterfactual explanations of already trained…