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pro vyhledávání: '"Versteeg, Philip"'
We consider the problem of discovering causal relations from independence constraints selection bias in addition to confounding is present. While the seminal FCI algorithm is sound and complete in this setup, no criterion for the causal interpretatio
Externí odkaz:
http://arxiv.org/abs/2203.01848
Autor:
Versteeg, Philip, Mooij, Joris M.
Publikováno v:
2019 IEEE Intl. Conf. Bioinf. and Biomed. (BIBM 2019) pp. 2599-2604
We study the performance of Local Causal Discovery (LCD), a simple and efficient constraint-based method for causal discovery, in predicting causal effects in large-scale gene expression data. We construct practical estimators specific to the high-di
Externí odkaz:
http://arxiv.org/abs/1910.02505
Autor:
Magliacane, Sara, van Ommen, Thijs, Claassen, Tom, Bongers, Stephan, Versteeg, Philip, Mooij, Joris M.
Publikováno v:
Advances in Neural Information Processing Systems 31 (NeurIPS*2018), 10869-10879
An important goal common to domain adaptation and causal inference is to make accurate predictions when the distributions for the source (or training) domain(s) and target (or test) domain(s) differ. In many cases, these different distributions can b
Externí odkaz:
http://arxiv.org/abs/1707.06422
Autor:
Meinshausen, Nicolai, Hauser, Alain, Mooij, Joris M., Peters, Jonas, Versteeg, Philip, Bühlmann, Peter
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America, 2016 Jul 01. 113(27), 7361-7368.
Externí odkaz:
https://www.jstor.org/stable/26470692
