Search results
Results: 6
Number of items: 6
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Blom, T., & Mooij, J. M. (2023). Causality and independence in perfectly adapted dynamical systems. Journal of Causal Inference, 11(1), Article 20210005. https://doi.org/10.1515/jci-2021-0005 -
Blom, T., & Mooij, J. M. (2022). Robustness of model predictions under extension. Proceedings of Machine Learning Research, 180, 213-222. https://openreview.net/forum?id=BGGevIUicl9
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Blom, T., Van Diepen, M., & Mooij, J. M. (2021). Conditional independences and causal relations implied by sets of equations. Journal of Machine Learning Research, 22(178), 1-62. http://jmlr.org/papers/v22/20-863.html
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Blom, T., Bongers, S., & Mooij, J. M. (2019). Beyond Structural Causal Models: Causal Constraints Models. In A. Globerson, & R. Silva (Eds.), Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence: UAI 2019, Tel Aviv, Israel, July 22-25, 2019 Article 205 AUAI Press. http://auai.org/uai2019/proceedings/papers/205.pdf
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Blom, T., Klimovskaia, A., Magliacane, S., & Mooij, J. M. (2018). An Upper Bound for Random Measurement Error in Causal Discovery. In A. Globerson, & R. Silva (Eds.), Uncertainty in Artificial Intelligence: proceedings of the Thirty-Fourth Concerence (2018) : August 6-10, 2018, Monterey, California, USA (pp. 570-579). AUAI Press. http://auai.org/uai2018/proceedings/papers/208.pdf
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