Jonas Wahl

German Research Centre for Artificial Intelligence — Germany

Computer Science · Physical Sciences

4h-index32citations30works0.22yr avg
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Research Topics

Bayesian Modeling and Causal Inference(15), Advanced Operator Algebra Research(8), Algebraic structures and combinatorial models(6), Advanced Graph Neural Networks(3), Noncommutative and Quantum Gravity Theories(3)

Publications30 total

Causal inference on process graphs: Causal structure and effect identification
Bernoulli·2026
Tropicalising hypergeometric $τ$-functions
arXiv (Cornell University)·2025Open Access
Causal discovery on vector-valued variables and consistency-guided aggregation
arXiv (Cornell University)·2025Open Access
When Counterfactual Reasoning Fails: Chaos and Real-World Complexity
arXiv (Cornell University)·2025Open Access
Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery
arXiv (Cornell University)·2025Open Access
Internal Incoherency Scores for Constraint-based Causal Discovery Algorithms
arXiv (Cornell University)·2025Open Access
The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications
arXiv (Cornell University)·2024· 1 citedOpen Access
Sortability of Time Series Data
arXiv (Cornell University)·2024Open Access
Asymptotic Uncertainty in the Estimation of Frequency Domain Causal Effects for Linear Processes
arXiv (Cornell University)·2024Open Access
Causal Inference on Process Graphs, Part II: Causal Structure and Effect Identification
arXiv (Cornell University)·2024Open Access
Impacts of Climate Change on Small Island Nations: A Data Science Framework using Remote Sensing and Observational Time Series
2024Open Access
Separation-based distance measures for causal graphs
arXiv (Cornell University)·2024Open Access
Foundations of causal discovery on groups of variables
Journal of Causal Inference·2024· 1 citedOpen Access
Invariance & Causal Representation Learning: Prospects and Limitations
arXiv (Cornell University)·2023Open Access
Identifying Linearly-Mixed Causal Representations from Multi-Node Interventions
arXiv (Cornell University)·2023Open Access
Projecting infinite time series graphs to finite marginal graphs using number theory
arXiv (Cornell University)·2023· 1 citedOpen Access
Vector Causal Inference between Two Groups of Variables
Proceedings of the AAAI Conference on Artificial Intelligence·2023· 4 citedOpen Access
Conditional Independence Testing with Heteroskedastic Data and Applications to Causal Discovery
arXiv (Cornell University)·2023Open Access
Foundations of Causal Discovery on Groups of Variables
arXiv (Cornell University)·2023Open Access
Causal Inference on Process Graphs, Part I: The Structural Equation Process Representation
arXiv (Cornell University)·2023Open Access
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Frequent Co-authors

Jakob Runge(16), Urmi Ninad(10), Andreas Gerhardus(5), Nicolas-Domenic Reiter(4), Yuki Arano(2), Tim de Laat(2), Sofia Faltenbacher(2), Rebecca Herman(2), Simon Bing(2), Pierre Tarrago(1), Stefaan Vaes(1), Philippe Brouillard(1), Chandler Squires(1), Konrad P. Körding(1), Karen Sachs(1), Alexandre Drouin(1), Dhanya Sridhar(1), C. Lohse(1), Marvin Anas Hahn(1), Brian O'Callaghan(1)