Richard Scheines

According to our database, Richard Scheines authored at least 31 papers between 1992 and 2018.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2018

Is the Doer Effect Robust Across Multiple Data Sets?

Kenneth R. Koedinger, Richard Scheines, Peter Schaldenbrand

Proceedings of the 11th International Conference on Educational Data Mining, 2018

2016

Measurement Error and Causal Discovery.

Richard Scheines, Joseph D. Ramsey

Proceedings of the UAI 2016 Workshop on Causation: Foundation to Application co-located with the 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), 2016

2015

The center for causal discovery of biomedical knowledge from big data.

Gregory F. Cooper, Ivet Bahar, Michael J. Becich, Panayiotis V. Benos, Jeremy M. Berg, Jeremy U. Espino, Clark Glymour, Rebecca Crowley Jacobson, Michelle Kienholz, Adrian V. Lee, Xinghua Lu, Richard Scheines

J. Am. Medical Informatics Assoc., 2015

2014

Causal Clustering for 2-Factor Measurement Models.

Erich Kummerfeld, Joe Ramsey, Renjie Yang, Peter Spirtes, Richard Scheines

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Discovering Prerequisite Relationships Among Knowledge Components.

Richard Scheines, Elizabeth Silver, Ilya M. Goldin

Proceedings of the 7th International Conference on Educational Data Mining, 2014

2013

Does Representational Understanding Enhance Fluency - Or Vice Versa? Searching for Mediation Models.

Martina A. Rau, Richard Scheines, Vincent Aleven, Nikol Rummel

Proceedings of the 6th International Conference on Educational Data Mining, 2013

Student Profiling from Tutoring System Log Data: When do Multiple Graphical Representations Matter?

Ryan Carlson, Konstantin Genin, Martina A. Rau, Richard Scheines

Proceedings of the 6th International Conference on Educational Data Mining, 2013

2012

Searching for Variables and Models to Investigate Mediators of Learning from Multiple Representations.

Martina A. Rau, Richard Scheines

Proceedings of the 5th International Conference on Educational Data Mining, 2012

2011

Using Tutors to Improve Educational Games.

Matthew W. Easterday, Vincent Aleven, Richard Scheines, Sharon M. Carver

Proceedings of the Artificial Intelligence in Education - 15th International Conference, 2011

2010

Actual causation: a stone soup essay.

Clark Glymour, David Danks, Bruce Glymour, Frederick Eberhardt, Joseph D. Ramsey, Richard Scheines, Peter Spirtes, Choh Man Teng, Jiji Zhang

Synth., 2010

Combining Experiments to Discover Linear Cyclic Models with Latent Variables.

Frederick Eberhardt, Patrik O. Hoyer, Richard Scheines

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Unsupervised Discovery of Student Strategies.

Benjamin Shih, Kenneth R. Koedinger, Richard Scheines

Proceedings of the Educational Data Mining 2010, 2010

2009

Constructing Causal Diagrams to Learn Deliberation.

Matthew W. Easterday, Vincent Aleven, Richard Scheines, Sharon M. Carver

Int. J. Artif. Intell. Educ., 2009

Will Google destroy western democracy? Bias in policy problem solving.

Matthew W. Easterday, Vincent Aleven, Richard Scheines, Sharon M. Carver

Proceedings of the Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling, 2009

2008

Causal discovery of linear acyclic models with arbitrary distributions.

Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu

Proceedings of the UAI 2008, 2008

A Response Time Model For Bottom-Out Hints as Worked Examples.

Benjamin Shih, Kenneth R. Koedinger, Richard Scheines

Proceedings of the Educational Data Mining 2008, 2008

2007

Optimizing Student Models for Causality.

Benjamin Shih, Kenneth R. Koedinger, Richard Scheines

Proceedings of the Artificial Intelligence in Education, 2007

'Tis Better to Construct than to Receive? The Effects of Diagram Tools on Causal Reasoning.

Matthew W. Easterday, Vincent Aleven, Richard Scheines

Proceedings of the Artificial Intelligence in Education, 2007

2006

Learning the Structure of Linear Latent Variable Models.

Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes

J. Mach. Learn. Res., 2006

Towards Association Rules with Hidden Variables.

Ricardo Bezerra de Andrade e Silva, Richard Scheines

Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

Bayesian learning of measurement and structural models.

Ricardo Bezerra de Andrade e Silva, Richard Scheines

Proceedings of the Machine Learning, 2006

2005

On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables.

Frederick Eberhardt, Clark Glymour, Richard Scheines

Proceedings of the UAI '05, 2005

New d-separation identification results for learning continuous latent variable models.

Ricardo Bezerra de Andrade e Silva, Richard Scheines

Proceedings of the Machine Learning, 2005

2003

A Statistical Problem for Inference to Regulatory Structure from Associations of Gene Expression Measurements with Microarrays.

Tianjiao Chu, Clark Glymour, Richard Scheines, Peter Spirtes

Bioinform., 2003

Learning Measurement Models for Unobserved Variables.

Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes

Proceedings of the UAI '03, 2003

2001

Semi-Instrumental Variables: A Test for Instrument Admissibility.

Tianjiao Chu, Richard Scheines, Peter Spirtes

Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Piecewise Linear Instrumental Variable Estimation of Causal Influence.

Richard Scheines, Gregory F. Cooper, Changwon Yoo, Tianjiao Chu

Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000

Causation, Prediction, and Search, Second Edition.

Peter Spirtes, Clark Glymour, Richard Scheines

Adaptive computation and machine learning, MIT Press, ISBN: 978-0-262-19440-2, 2000

1997

Estimating Latent Causal Inferences: Tetrad II model selection and Bayesian parameter estimation.

Richard Scheines

Proceedings of the Sixth International Workshop on Artificial Intelligence and Statistics, 1997

1994

Computer Environments for Proof Construction.

Richard Scheines, Wilfried Sieg

Interact. Learn. Environ., 1994

1992

Finding latent variable models in large databases.

Richard Scheines, Peter Spirtes

Int. J. Intell. Syst., 1992