Identifiability of Causal Graphs using Functional Models

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Standard

Identifiability of Causal Graphs using Functional Models. / Peters, Jonas Martin; Mooij, J.M.; Janzing, D.; Schölkopf, B.

Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI). 2011. p. 589-598.

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

Harvard

Peters, JM, Mooij, JM, Janzing, D & Schölkopf, B 2011, Identifiability of Causal Graphs using Functional Models. in Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI). pp. 589-598.

APA

Peters, J. M., Mooij, J. M., Janzing, D., & Schölkopf, B. (2011). Identifiability of Causal Graphs using Functional Models. In Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI) (pp. 589-598)

Vancouver

Peters JM, Mooij JM, Janzing D, Schölkopf B. Identifiability of Causal Graphs using Functional Models. In Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI). 2011. p. 589-598

Author

Peters, Jonas Martin ; Mooij, J.M. ; Janzing, D. ; Schölkopf, B. / Identifiability of Causal Graphs using Functional Models. Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI). 2011. pp. 589-598

Bibtex

@inbook{4ff2cd0e598740a69f418e2a00e69493,
title = "Identifiability of Causal Graphs using Functional Models",
author = "Peters, {Jonas Martin} and J.M. Mooij and D. Janzing and B. Sch{\"o}lkopf",
year = "2011",
language = "Udefineret/Ukendt",
pages = "589--598",
booktitle = "Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI)",

}

RIS

TY - CHAP

T1 - Identifiability of Causal Graphs using Functional Models

AU - Peters, Jonas Martin

AU - Mooij, J.M.

AU - Janzing, D.

AU - Schölkopf, B.

PY - 2011

Y1 - 2011

M3 - Bidrag til bog/antologi

SP - 589

EP - 598

BT - Proceedings of the 27th Annual Conference on Uncertainty in Artificial Intelligence (UAI)

ER -

ID: 165943484