Causal discovery for linear cyclic models with latent variables

Proceedings of the 5th European Workshop on Probabilistic Graphical Models, PGM 2010

Volumn , Issue , 2010, Pages 153-160

  Hyttinen, Antti ^a   Eberhardt, Frederick ^b   Hoyer, Patrik O ^a,c  

^a UNIVERSITY OF HELSINKI   (Finland)

^b WASHINGTON UNIVERSITY   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADDITIONAL STRUCTURES; CAUSAL RELATIONSHIPS; FEED-BACK LOOP; IDENTIFIABILITY CONDITIONS; LATENT VARIABLE; PRIOR KNOWLEDGE; PROTEIN SIGNALING; RANDOMIZED EXPERIMENTS; SEARCH SPACES;

EXPERIMENTS; LINEAR SYSTEMS;

DATA INTEGRATION;

EID: 84874736159     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (9)

1. K. A. Bollen. 1989. Structural Equations with Latent Variables. John Wiley & Sons.
2. F. Eberhardt, P. O. Hoyer, and R. Scheines. 2010. Combining experiments to discover linear cyclic models with latent variables. In AISTATS 2010.
3. S. Itani, M. Ohannessian, K. Sachs, G. P. Nolan, and M. A. Dahleh. 2010. Structure learning in causal cyclic networks. In JMLR W&CP, volume 6, pages 165-176.
4. J. Pearl. 2000. Causality. Oxford University Press.
5. T. Richardson. 1996. Feedback Models: Interpretation and Discovery. Ph.D. thesis, Carnegie Mellon.
6. K. Sachs, O. Perez, D. Pe'er, D.A. Lauffenburger, and G.P. Nolan. 2005. Causal protein-signaling networks derived from multiparameter single-cell data. Science, 308(5721):523-529.
7. M. Schmidt and K. Murphy. 2009. Modeling discrete interventional data using directed cyclic graphical models. In UAI '09.
8. P. Spirtes, C. Glymour, and R. Scheines. 2000. Causation, Prediction and Search. MIT Press, 2 edition.
9. P. Spirtes. 1995. Directed cyclic graphical representation of feedback models. In UAI'95.