Stebėti
Jonas Schweisthal
Jonas Schweisthal
PhD Student, LMU Munich
Patvirtintas el. paštas lmu.de - Pagrindinis puslapis
Pavadinimas
Cituota
Cituota
Metai
Causal machine learning for predicting treatment outcomes
S Feuerriegel, D Frauen, V Melnychuk, J Schweisthal, K Hess, A Curth, ...
Nature Medicine 30 (4), 958-968, 2024
1002024
Reliable Off-Policy Learning for Dosage Combinations
J Schweisthal, D Frauen, V Melnychuk, S Feuerriegel
Advances in Neural Information Processing Systems (NeurIPS), 2023
92023
Using natural language processing to analyse text data in behavioural science
S Feuerriegel, A Maarouf, D Bär, D Geissler, J Schweisthal, N Pröllochs, ...
Nature Reviews Psychology, 1-16, 2025
42025
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
42024
Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments
J Schweisthal, D Frauen, M van der Schaar, S Feuerriegel
International Conference on Machine Learning (ICML), 2024
32024
Robust and efficient imbalanced positive-unlabeled learning with self-supervision
E Dorigatti, J Schweisthal, B Bischl, M Rezaei
arXiv preprint arXiv:2209.02459, 2022
22022
Orthogonal representation learning for estimating causal quantities
V Melnychuk, D Frauen, J Schweisthal, S Feuerriegel
arXiv preprint arXiv:2502.04274, 2025
12025
DiffPO: A causal diffusion model for learning distributions of potential outcomes
Y Ma, V Melnychuk, J Schweisthal, S Feuerriegel
Advances in Neural Information Processing Systems (NeurIPS), 2024
12024
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
2025
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
Predicting the Validity and Reliability of Survey Questions
B Felderer, L Repke, W Weber, J Schweisthal, L Bothmann
OSF Preprints, 2024
2024
Self-supervised Learning Framework for Imbalanced Positive-Unlabeled Data
J Schweisthal
2022
Prädiktion mit Alters-Perioden-Kohorten-Modellen
J Schweisthal
2019
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Straipsniai 1–13