| Post-hoc saliency methods fail to capture latent feature importance in time series data M Schröder, A Zamanian, N Ahmidi International Workshop on Trustworthy Machine Learning for Healthcare, 106-121, 2023 | 8 | 2023 |
| Causal fairness under unobserved confounding: A neural sensitivity framework M Schröder, D Frauen, S Feuerriegel ICLR, 2024 | 6 | 2024 |
| Automatic gait analysis during steady and unsteady walking using a smartphone A Sher, D Langford, E Dogger, D Monaghan, LI Lunn, M Schroeder, ... Authorea Preprints, 2021 | 5 | 2021 |
| Conformal prediction for causal effects of continuous treatments M Schröder, D Frauen, J Schweisthal, K Heß, V Melnychuk, S Feuerriegel arXiv preprint arXiv:2407.03094, 2024 | 4 | 2024 |
| What about the Latent Space? The Need for Latent Feature Saliency Detection in Deep Time Series Classification M Schröder, A Zamanian, N Ahmidi Machine Learning and Knowledge Extraction 5 (2), 539-559, 2023 | 4 | 2023 |
| Differentially private learners for heterogeneous treatment effects M Schröder, V Melnychuk, S Feuerriegel The Thirteenth International Conference on Learning Representations, 2025 | | 2025 |
| Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets Y Wang, M Schröder, D Frauen, J Schweisthal, K Hess, S Feuerriegel International Conference on Learning Representations (ICLR) 2025, 2024 | | 2024 |
| Learning Representations of Instruments for Partial Identification of Treatment Effects J Schweisthal, D Frauen, M Schröder, K Hess, N Kilbertus, S Feuerriegel arXiv preprint arXiv:2410.08976, 2024 | | 2024 |
Stefan FeuerriegelProfessor, LMU MunichVerified email at lmu.de
