Richard Scheines

Affiliations:
  • Carnegie Mellon University, Pittsburgh, USA


According to our database1, Richard Scheines authored at least 30 papers between 1992 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2018
Is the Doer Effect Robust Across Multiple Data Sets?
Proceedings of the 11th International Conference on Educational Data Mining, 2018

2016
Measurement Error and Causal Discovery.
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.
J. Am. Medical Informatics Assoc., 2015

2014
Causal Clustering for 2-Factor Measurement Models.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2014

Discovering Prerequisite Relationships Among Knowledge Components.
Proceedings of the 7th International Conference on Educational Data Mining, 2014

2013
Does Representational Understanding Enhance Fluency - Or Vice Versa? Searching for Mediation Models.
Proceedings of the 6th International Conference on Educational Data Mining, 2013

Student Profiling from Tutoring System Log Data: When do Multiple Graphical Representations Matter?
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.
Proceedings of the 5th International Conference on Educational Data Mining, 2012

2011
Using Tutors to Improve Educational Games.
Proceedings of the Artificial Intelligence in Education - 15th International Conference, 2011

2010
Actual causation: a stone soup essay.
Synth., 2010

Combining Experiments to Discover Linear Cyclic Models with Latent Variables.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

Unsupervised Discovery of Student Strategies.
Proceedings of the Educational Data Mining 2010, 2010

2009
Constructing Causal Diagrams to Learn Deliberation.
Int. J. Artif. Intell. Educ., 2009

Will Google destroy western democracy? Bias in policy problem solving.
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.
Proceedings of the UAI 2008, 2008

A Response Time Model For Bottom-Out Hints as Worked Examples.
Proceedings of the Educational Data Mining 2008, 2008

2007
Optimizing Student Models for Causality.
Proceedings of the Artificial Intelligence in Education, 2007

'Tis Better to Construct than to Receive? The Effects of Diagram Tools on Causal Reasoning.
Proceedings of the Artificial Intelligence in Education, 2007

2006
Learning the Structure of Linear Latent Variable Models.
J. Mach. Learn. Res., 2006

Towards Association Rules with Hidden Variables.
Proceedings of the Knowledge Discovery in Databases: PKDD 2006, 2006

Bayesian learning of measurement and structural models.
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.
Proceedings of the UAI '05, 2005

New d-separation identification results for learning continuous latent variable models.
Proceedings of the Machine Learning, 2005

2003
A Statistical Problem for Inference to Regulatory Structure from Associations of Gene Expression Measurements with Microarrays.
Bioinform., 2003

Learning Measurement Models for Unobserved Variables.
Proceedings of the UAI '03, 2003

2001
Semi-Instrumental Variables: A Test for Instrument Admissibility.
Proceedings of the UAI '01: Proceedings of the 17th Conference in Uncertainty in Artificial Intelligence, 2001

Piecewise Linear Instrumental Variable Estimation of Causal Influence.
Proceedings of the Eighth International Workshop on Artificial Intelligence and Statistics, 2001

2000
Causation, Prediction, and Search, Second Edition.
Adaptive computation and machine learning, MIT Press, ISBN: 978-0-262-19440-2, 2000

1994
Computer Environments for Proof Construction.
Interact. Learn. Environ., 1994

1992
Finding latent variable models in large databases.
Int. J. Intell. Syst., 1992


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