Jonas Schweisthal

According to our database, Jonas Schweisthal authored at least 13 papers between 2022 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

LLM-Driven Treatment Effect Estimation Under Inference Time Text Confounding.

Yuchen Ma, Dennis Frauen, Jonas Schweisthal, Stefan Feuerriegel

CoRR, July, 2025

A Diffusion-Based Method for Learning the Multi-Outcome Distribution of Medical Treatments.

Yuchen Ma, Jonas Schweisthal, Hengrui Zhang, Stefan Feuerriegel

CoRR, June, 2025

Algorithms for reliable decision-making need causal reasoning.

Christoph Kern, Unai Fischer Abaigar, Jonas Schweisthal, Dennis Frauen, Rayid Ghani, Stefan Feuerriegel, Mihaela van der Schaar, Frauke Kreuter

Nat. Comput. Sci., May, 2025

Treatment Effect Estimation for Optimal Decision-Making.

Dennis Frauen, Valentyn Melnychuk, Jonas Schweisthal, Mihaela van der Schaar, Stefan Feuerriegel

CoRR, May, 2025

Orthogonal Representation Learning for Estimating Causal Quantities.

Valentyn Melnychuk, Dennis Frauen, Jonas Schweisthal, Stefan Feuerriegel

CoRR, February, 2025

Constructing Confidence Intervals for Average Treatment Effects from Multiple Datasets.

Yuxin Wang, Maresa Schröder, Dennis Frauen, Jonas Schweisthal, Konstantin Hess, Stefan Feuerriegel

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

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

Causal machine learning for predicting treatment outcomes.

Stefan Feuerriegel, Dennis Frauen, Valentyn Melnychuk, Jonas Schweisthal, Konstantin Hess, Alicia Curth, Stefan Bauer, Niki Kilbertus, Isaac S. Kohane, Mihaela van der Schaar

CoRR, 2024

Conformal Prediction for Causal Effects of Continuous Treatments.

Maresa Schröder, Dennis Frauen, Jonas Schweisthal, Konstantin Hess, Valentyn Melnychuk, Stefan Feuerriegel

CoRR, 2024

DiffPO: A causal diffusion model for learning distributions of potential outcomes.

Yuchen Ma, Valentyn Melnychuk, Jonas Schweisthal, Stefan Feuerriegel

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Meta-Learners for Partially-Identified Treatment Effects Across Multiple Environments.

Jonas Schweisthal, Dennis Frauen, Mihaela van der Schaar, Stefan Feuerriegel

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Reliable Off-Policy Learning for Dosage Combinations.

Jonas Schweisthal, Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervision.

Emilio Dorigatti, Jonas Schweisthal, Bernd Bischl, Mina Rezaei

CoRR, 2022