Causality
Causal discovery aims to automatically uncover causal relationships from data, a capability with significant potential across many …
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URL
@inproceedings{brouillardTheLandscapeOfCausal2025,
author = {Philippe Brouillard and Chandler Squires and Jonas Wahl and Konrad Körding and Karen Sachs and Alexandre Drouin and Dhanya Sridhar},
booktitle = {Proceedings of the Fourth Conference on Causal Learning and Reasoning. Conference on Causal Learning and Reasoning (CLeaR-2025)},
organization = {PMLR},
pages = {834-873},
publisher = {MLResearchPress},
title = {The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applications},
url = {https://proceedings.mlr.press/v275/brouillard25a},
volume = {275},
year = {2025}
}
Causal discovery aims to extract qualitative causal knowledge in the form of causal graphs from data. Because causal ground truth is …
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URL
@inproceedings{hermanUnitlessUnrestrictedMarkovConsistentSCM2025,
author = {Rebecca J Herman and Jonas Wahl and Urmi Ninad and Jakob Runge},
booktitle = {Proceedings of the Fourth Conference on Causal Learning and Reasoning. Conference on Causal Learning and Reasoning (CLeaR-2025)},
pages = {1506-1531},
publisher = {MLResearchPress},
title = {Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discovery},
url = {https://proceedings.mlr.press/v275/herman25a.html},
volume = {275},
year = {2025}
}