Finding latent variable models in large databases. - Richard Scheines; Peter Spirtes (Int. J. Intell. Syst., 1992)

Computer Environments for Proof Construction. - Richard Scheines; Wilfried Sieg (Interact. Learn. Environ., 1994)

Estimating Latent Causal Inferences: Tetrad II model selection and Bayesian parameter estimation. - Richard Scheines (AISTATS, 1997)

Causation, Prediction, and Search, Second Edition. - Peter Spirtes; Clark Glymour; Richard Scheines (MIT Press, 2000)

Piecewise Linear Instrumental Variable Estimation of Causal Influence. - Richard Scheines; Gregory F. Cooper; Changwon Yoo; Tianjiao Chu (AISTATS, 2001)

Semi-Instrumental Variables: A Test for Instrument Admissibility. - Tianjiao Chu; Richard Scheines; Peter Spirtes (UAI, 2001)

Learning Measurement Models for Unobserved Variables. - Ricardo Bezerra de Andrade e Silva; Richard Scheines; Clark Glymour; Peter Spirtes (UAI, 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)

New d-separation identification results for learning continuous latent variable models. - Ricardo Bezerra de Andrade e Silva; Richard Scheines (ICML, 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 (UAI, 2005)

Bayesian learning of measurement and structural models. - Ricardo Bezerra de Andrade e Silva; Richard Scheines (ICML, 2006)

Towards Association Rules with Hidden Variables. - Ricardo Bezerra de Andrade e Silva; Richard Scheines (PKDD, 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)

'Tis Better to Construct than to Receive? The Effects of Diagram Tools on Causal Reasoning. - Matthew W. Easterday; Vincent Aleven; Richard Scheines (AIED, 2007)

Optimizing Student Models for Causality. - Benjamin Shih; Kenneth R. Koedinger; Richard Scheines (AIED, 2007)

A Response Time Model For Bottom-Out Hints as Worked Examples. - Benjamin Shih; Kenneth R. Koedinger; Richard Scheines (EDM, 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 (UAI, 2008)

Will Google destroy western democracy? Bias in policy problem solving. - Matthew W. Easterday; Vincent Aleven; Richard Scheines; Sharon M. Carver (AIED, 2009)

Constructing Causal Diagrams to Learn Deliberation. - Matthew W. Easterday; Vincent Aleven; Richard Scheines; Sharon M. Carver (Int. J. Artif. Intell. Educ., 2009)

Unsupervised Discovery of Student Strategies. - Benjamin Shih; Kenneth R. Koedinger; Richard Scheines (EDM, 2010)

Combining Experiments to Discover Linear Cyclic Models with Latent Variables. - Frederick Eberhardt; Patrik O. Hoyer; Richard Scheines (AISTATS, 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 001; Jiji Zhang (Synth., 2010)

Using Tutors to Improve Educational Games. - Matthew W. Easterday; Vincent Aleven; Richard Scheines; Sharon M. Carver (AIED, 2011)

Searching for Variables and Models to Investigate Mediators of Learning from Multiple Representations. - Martina A. Rau; Richard Scheines (EDM, 2012)

Student Profiling from Tutoring System Log Data: When do Multiple Graphical Representations Matter? - Ryan Carlson; Konstantin Genin; Martina A. Rau; Richard Scheines (EDM, 2013)

Does Representational Understanding Enhance Fluency - Or Vice Versa? Searching for Mediation Models. - Martina A. Rau; Richard Scheines; Vincent Aleven; Nikol Rummel (EDM, 2013)

Discovering Prerequisite Relationships Among Knowledge Components. - Richard Scheines; Elizabeth Silver; Ilya M. Goldin (EDM, 2014)

Causal Clustering for 2-Factor Measurement Models. - Erich Kummerfeld; Joe Ramsey; Renjie Yang; Peter Spirtes; Richard Scheines (ECML/PKDD (2), 2014)

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 001; Richard Scheines (J. Am. Medical Informatics Assoc., 2015)

Measurement Error and Causal Discovery. - Richard Scheines; Joseph D. Ramsey (CFA@UAI, 2016)

Is the Doer Effect Robust Across Multiple Data Sets? - Kenneth R. Koedinger; Richard Scheines; Peter Schaldenbrand (EDM, 2018)