Jonas Wahl

According to our database, Jonas Wahl authored at least 17 papers between 2021 and 2025.

Collaborative distances:

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

2025

When Counterfactual Reasoning Fails: Chaos and Real-World Complexity.

Yahya Aalaila, Gerrit Großmann, Sumantrak Mukherjee, Jonas Wahl, Sebastian J. Vollmer

CoRR, March, 2025

Internal Incoherency Scores for Constraint-based Causal Discovery Algorithms.

Sofia Faltenbacher, Jonas Wahl, Rebecca Herman, Jakob Runge

CoRR, February, 2025

Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery.

Rebecca Herman, Jonas Wahl, Urmi Ninad, Jakob Runge

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications.

Philippe Brouillard, Chandler Squires, Jonas Wahl, Konrad K, Karen Sachs, Alexandre Drouin, Dhanya Sridhar

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

Separation-Based Distance Measures for Causal Graphs.

Jonas Wahl, Jakob Runge

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2025

2024

Invariance & Causal Representation Learning: Prospects and Limitations.

Simon Bing, Tom Hochsprung, Jonas Wahl, Urmi Ninad, Jakob Runge

Trans. Mach. Learn. Res., 2024

Causal Inference for Spatial Data Analytics (Dagstuhl Seminar 24202).

Martin Tomko, Yanan Xin, Jonas Wahl

Dagstuhl Reports, 2024

The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications.

Philippe Brouillard, Chandler Squires, Jonas Wahl, Konrad P. Kording, Karen Sachs, Alexandre Drouin, Dhanya Sridhar

CoRR, 2024

Sortability of Time Series Data.

Christopher Lohse, Jonas Wahl

CoRR, 2024

Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions.

Simon Bing, Urmi Ninad, Jonas Wahl, Jakob Runge

Proceedings of the Causal Learning and Reasoning, 2024

2023

Invariance & Causal Representation Learning: Prospects and Limitations.

Simon Bing, Jonas Wahl, Urmi Ninad, Jakob Runge

CoRR, 2023

Projecting infinite time series graphs to finite marginal graphs using number theory.

Andreas Gerhardus, Jonas Wahl, Sofia Faltenbacher, Urmi Ninad, Jakob Runge

CoRR, 2023

Increasing effect sizes of pairwise conditional independence tests between random vectors.

Tom Hochsprung, Jonas Wahl, Andreas Gerhardus, Urmi Ninad, Jakob Runge

Proceedings of the Uncertainty in Artificial Intelligence, 2023

Vector Causal Inference between Two Groups of Variables.

Jonas Wahl, Urmi Ninad, Jakob Runge

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Where are all the guns? Modeling firearm ownership in the United States.

Jonas Wahl

Patterns, 2022

Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery.

Wiebke Günther, Urmi Ninad, Jonas Wahl, Jakob Runge

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Explainability Auditing for Intelligent Systems: A Rationale for Multi-Disciplinary Perspectives.

Markus Langer, Kevin Baum, Kathrin Hartmann, Stefan Hessel, Timo Speith, Jonas Wahl

Proceedings of the 29th IEEE International Requirements Engineering Conference Workshops, 2021