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Title:

Confidence in causal discovery with linear causal models

Document type:
Konferenzbeitrag
Contribution type:
Vortrag / Präsentation
Author(s):
Strieder, David; Freidling, Tobias; Haffner, Stefan; Drton, Mathias
Pages contribution:
1217-1226
Abstract:
Structural causal models postulate noisy functional relations among a set of interacting variables. The causal structure underlying each such model is naturally represented by a directed graph whose edges indicate for each variable which other variables it causally depends upon. Under a number of different model assumptions, it has been shown that this causal graph and, thus also, causal effects are identifiable from mere observational data. For these models, practical algorithms have been devis...     »
Dewey Decimal Classification:
510 Mathematik
Editor:
MLResearchPress
Book / Congress title:
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence
Volume:
161
Date of congress:
27-30 July 2021
Date of publication:
01.07.2021
Year:
2021
Quarter:
3. Quartal
Year / month:
2021-07
Month:
Jul
Language:
en
Publication format:
WWW
WWW:
Proceedings of Machine Learning Research
Semester:
SS 21
TUM Institution:
Lehrstuhl für Mathematische Statistik
Format:
Text
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