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Popescu, Oana and Gerhardus, Andreas and Rabel, Martin and Runge, Jakob (2025) Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation. In: 4th Conference on Causal Learning and Reasoning, CLeaR 2025, 275, pp. 406-450. Proceedings of Machine Learning Research. CLeaR (Causal Learning and Reasoning) 2025, 2025-05-07 - 2025-05-09, Lausanne, Schweiz. ISSN 2640-3498.
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Official URL: https://proceedings.mlr.press/v275/popescu25a.html
| Item URL in elib: | https://elib.dlr.de/220071/ | ||||||||||||||||||||
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| Document Type: | Conference or Workshop Item (Poster) | ||||||||||||||||||||
| Title: | Non-parametric Conditional Independence Testing for Mixed Continuous-Categorical Variables: A Novel Method and Numerical Evaluation | ||||||||||||||||||||
| Authors: |
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| Date: | May 2025 | ||||||||||||||||||||
| Journal or Publication Title: | 4th Conference on Causal Learning and Reasoning, CLeaR 2025 | ||||||||||||||||||||
| Refereed publication: | Yes | ||||||||||||||||||||
| Open Access: | No | ||||||||||||||||||||
| Gold Open Access: | No | ||||||||||||||||||||
| In SCOPUS: | Yes | ||||||||||||||||||||
| In ISI Web of Science: | No | ||||||||||||||||||||
| Volume: | 275 | ||||||||||||||||||||
| Page Range: | pp. 406-450 | ||||||||||||||||||||
| Editors: |
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| Publisher: | Proceedings of Machine Learning Research | ||||||||||||||||||||
| Series Name: | Proceedings of Machine Learning Research | ||||||||||||||||||||
| ISSN: | 2640-3498 | ||||||||||||||||||||
| Status: | Published | ||||||||||||||||||||
| Keywords: | conditional independence testing, conditional mutual information, mixed-type data | ||||||||||||||||||||
| Event Title: | CLeaR (Causal Learning and Reasoning) 2025 | ||||||||||||||||||||
| Event Location: | Lausanne, Schweiz | ||||||||||||||||||||
| Event Type: | international Conference | ||||||||||||||||||||
| Event Start Date: | 7 May 2025 | ||||||||||||||||||||
| Event End Date: | 9 May 2025 | ||||||||||||||||||||
| HGF - Research field: | Aeronautics, Space and Transport | ||||||||||||||||||||
| HGF - Program: | Space | ||||||||||||||||||||
| HGF - Program Themes: | other | ||||||||||||||||||||
| DLR - Research area: | Raumfahrt | ||||||||||||||||||||
| DLR - Program: | R - no assignment | ||||||||||||||||||||
| DLR - Research theme (Project): | R - no assignment, D - CausalAnomalies | ||||||||||||||||||||
| Location: | Jena | ||||||||||||||||||||
| Institutes and Institutions: | Institute of Data Science > Data Analysis and Intelligence | ||||||||||||||||||||
| Deposited By: | Gerhardus, Andreas | ||||||||||||||||||||
| Deposited On: | 05 Dec 2025 14:21 | ||||||||||||||||||||
| Last Modified: | 13 Mar 2026 13:46 |
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