| 2008 |
|---|
| 11 | EE | Patrik O. Hoyer,
Aapo Hyvärinen,
Richard Scheines,
Peter Spirtes,
Joseph Ramsey,
Gustavo Lacerda,
Shohei Shimizu:
Causal discovery of linear acyclic models with arbitrary distributions.
UAI 2008: 282-289 |
| 2007 |
|---|
| 10 | | Benjamin Shih,
Kenneth R. Koedinger,
Richard Scheines:
Optimizing Student Models for Causality.
AIED 2007: 644-646 |
| 9 | | Matthew W. Easterday,
Vincent Aleven,
Richard Scheines:
'Tis Better to Construct than to Receive? The Effects of Diagram Tools on Causal Reasoning.
AIED 2007: 93-100 |
| 2006 |
|---|
| 8 | EE | Ricardo Silva,
Richard Scheines:
Bayesian learning of measurement and structural models.
ICML 2006: 825-832 |
| 7 | EE | Ricardo Silva,
Richard Scheines:
Towards Association Rules with Hidden Variables.
PKDD 2006: 617-624 |
| 6 | EE | Ricardo Silva,
Richard Scheines,
Clark Glymour,
Peter Spirtes:
Learning the Structure of Linear Latent Variable Models.
Journal of Machine Learning Research 7: 191-246 (2006) |
| 2005 |
|---|
| 5 | EE | Ricardo Silva,
Richard Scheines:
New d-separation identification results for learning continuous latent variable models.
ICML 2005: 808-815 |
| 4 | EE | Frederick Eberhardt,
Clark Glymour,
Richard Scheines:
On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables.
UAI 2005: 178-184 |
| 2003 |
|---|
| 3 | | Ricardo Bezerra de Andrade e Silva,
Richard Scheines,
Clark Glymour,
Peter Spirtes:
Learning Measurement Models for Unobserved Variables.
UAI 2003: 543-550 |
| 2 | | Tianjiao Chu,
Clark Glymour,
Richard Scheines,
Peter Spirtes:
A Statistical Problem for Inference to Regulatory Structure from Associations of Gene Expression Measurements with Microarrays.
Bioinformatics 19(9): 1147-1152 (2003) |
| 2001 |
|---|
| 1 | EE | Tianjiao Chu,
Richard Scheines,
Peter Spirtes:
Semi-Instrumental Variables: A Test for Instrument Admissibility.
UAI 2001: 83-90 |
