Post-hoc Saliency Methods Fail to Capture Latent Feature Importance in Time Series Data. - Maresa Schröder; Alireza Zamanian; Narges Ahmidi (TML4H, 2023)

What about the Latent Space? The Need for Latent Feature Saliency Detection in Deep Time Series Classification. - Maresa Schröder; Alireza Zamanian; Narges Ahmidi (Mach. Learn. Knowl. Extr., 2023)

Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework. - Maresa Schröder; Dennis Frauen; Stefan Feuerriegel (ICLR, 2024)

Conformal Prediction for Causal Effects of Continuous Treatments. - Maresa Schröder; Dennis Frauen; Jonas Schweisthal; Konstantin Hess; Valentyn Melnychuk; Stefan Feuerriegel (CoRR, 2024)

Learning Representations of Instruments for Partial Identification of Treatment Effects. - Jonas Schweisthal; Dennis Frauen; Maresa Schröder; Konstantin Hess; Niki Kilbertus; Stefan Feuerriegel (CoRR, 2024)

Differentially private learners for heterogeneous treatment effects. - Maresa Schröder; Valentyn Melnychuk; Stefan Feuerriegel (ICLR, 2025)

Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets. - Yuxin Wang; Maresa Schröder; Dennis Frauen; Jonas Schweisthal; Konstantin Hess; Stefan Feuerriegel (ICLR, 2025)

Orthogonal Survival Learners for Estimating Heterogeneous Treatment Effects from Time-to-Event Data. - Dennis Frauen; Maresa Schröder; Konstantin Hess; Stefan Feuerriegel (CoRR, 2025)

PrivATE: Differentially Private Confidence Intervals for Average Treatment Effects. - Maresa Schröder; Justin Hartenstein; Stefan Feuerriegel (CoRR, 2025)