| Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies M Kuzmanovic, T Hatt, S Feuerriegel Machine Learning for Health (ML4H), 2021 | 18 | 2021 |
| Estimating conditional average treatment effects with missing treatment information M Kuzmanovic, T Hatt, S Feuerriegel International Conference on Artificial Intelligence and Statistics, 746-766, 2023 | 9 | 2023 |
| Causal Machine Learning for Cost-Effective Allocation of Development Aid M Kuzmanovic, D Frauen, T Hatt, S Feuerriegel arXiv preprint arXiv:2401.16986, 2024 | | 2024 |
| Addressing distributional shifts in operations management: The case of order fulfillment in customized production J Senoner, B Kratzwald, M Kuzmanovic, TH Netland, S Feuerriegel Production and Operations Management 32 (10), 3022-3042, 2023 | | 2023 |
| Advances in Causal Machine Learning for Health Management M Kuzmanovic ETH Zurich, 2022 | | 2022 |
| Path Signatures in Machine Learning-based Analysis of Financial Time Series M Kuzmanovic Universität St. Gallen, 2018 | | 2018 |
Stefan FeuerriegelProfessor, LMU MunichBestätigte E-Mail-Adresse bei lmu.de
