Richard Scheines

35 papers A* 2A 11B 7Journal 11Unranked 3

Year	Rank	Type	Title / Venue / Authors
2018	B	`conf`	Is the Doer Effect Robust Across Multiple Data Sets? EDM Kenneth R. Koedinger, Richard Scheines, Peter Schaldenbrand
2016	—	`conf`	Measurement Error and Causal Discovery. CFA@UAI Richard Scheines, Joseph D. Ramsey
2015	J	`jnl`	The center for causal discovery of biomedical knowledge from big data. J. Am. Medical Informatics Assoc. 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
2014	—	`conf`	Causal Clustering for 2-Factor Measurement Models. ECML/PKDD (2) Erich Kummerfeld, Joe Ramsey, Renjie Yang, Peter Spirtes, Richard Scheines
2014	B	`conf`	Discovering Prerequisite Relationships Among Knowledge Components. EDM Richard Scheines, Elizabeth Silver, Ilya M. Goldin
2013	B	`conf`	Does Representational Understanding Enhance Fluency - Or Vice Versa? Searching for Mediation Models. EDM Martina A. Rau, Richard Scheines, Vincent Aleven, Nikol Rummel
2013	J	`jnl`	Semi-Instrumental Variables: A Test for Instrument Admissibility CoRR Tianjiao Chu, Richard Scheines, Peter Spirtes
2013	B	`conf`	Student Profiling from Tutoring System Log Data: When do Multiple Graphical Representations Matter? EDM Ryan Carlson, Konstantin Genin, Martina A. Rau, Richard Scheines
2012	J	`jnl`	Causal discovery of linear acyclic models with arbitrary distributions CoRR Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu
2012	J	`jnl`	Learning Measurement Models for Unobserved Variables CoRR Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
2012	J	`jnl`	On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables CoRR Frederick Eberhardt, Clark Glymour, Richard Scheines
2012	B	`conf`	Searching for Variables and Models to Investigate Mediators of Learning from Multiple Representations. EDM Martina A. Rau, Richard Scheines
2011	A	`conf`	Using Tutors to Improve Educational Games. AIED Matthew W. Easterday, Vincent Aleven, Richard Scheines, Sharon M. Carver
2010	J	`jnl`	Actual causation: a stone soup essay. Synth. Clark Glymour, David Danks, Bruce Glymour, Frederick Eberhardt, Joseph D. Ramsey, Richard Scheines, Peter Spirtes, Choh Man Teng, Jiji Zhang
2010	A	`conf`	Combining Experiments to Discover Linear Cyclic Models with Latent Variables. AISTATS Frederick Eberhardt, Patrik O. Hoyer, Richard Scheines
2010	B	`conf`	Unsupervised Discovery of Student Strategies. EDM Benjamin Shih, Kenneth R. Koedinger, Richard Scheines
2009	J	`jnl`	Constructing Causal Diagrams to Learn Deliberation. Int. J. Artif. Intell. Educ. Matthew W. Easterday, Vincent Aleven, Richard Scheines, Sharon M. Carver
2009	A	`conf`	Will Google destroy western democracy? Bias in policy problem solving. AIED Matthew W. Easterday, Vincent Aleven, Richard Scheines, Sharon M. Carver
2008	B	`conf`	A Response Time Model For Bottom-Out Hints as Worked Examples. EDM Benjamin Shih, Kenneth R. Koedinger, Richard Scheines
2008	A	`conf`	Causal discovery of linear acyclic models with arbitrary distributions. UAI Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu
2007	A	`conf`	'Tis Better to Construct than to Receive? The Effects of Diagram Tools on Causal Reasoning. AIED Matthew W. Easterday, Vincent Aleven, Richard Scheines
2007	A	`conf`	Optimizing Student Models for Causality. AIED Benjamin Shih, Kenneth R. Koedinger, Richard Scheines
2006	A*	`conf`	Bayesian learning of measurement and structural models. ICML Ricardo Bezerra de Andrade e Silva, Richard Scheines
2006	J	`jnl`	Learning the Structure of Linear Latent Variable Models. J. Mach. Learn. Res. Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
2006	—	`conf`	Towards Association Rules with Hidden Variables. PKDD Ricardo Bezerra de Andrade e Silva, Richard Scheines
2005	A*	`conf`	New d-separation identification results for learning continuous latent variable models. ICML Ricardo Bezerra de Andrade e Silva, Richard Scheines
2005	A	`conf`	On the Number of Experiments Sufficient and in the Worst Case Necessary to Identify All Causal Relations Among N Variables. UAI Frederick Eberhardt, Clark Glymour, Richard Scheines
2003	J	`jnl`	A Statistical Problem for Inference to Regulatory Structure from Associations of Gene Expression Measurements with Microarrays. Bioinform. Tianjiao Chu, Clark Glymour, Richard Scheines, Peter Spirtes
2003	A	`conf`	Learning Measurement Models for Unobserved Variables. UAI Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
2001	A	`conf`	Piecewise Linear Instrumental Variable Estimation of Causal Influence. AISTATS Richard Scheines, Gregory F. Cooper, Changwon Yoo, Tianjiao Chu
2001	A	`conf`	Semi-Instrumental Variables: A Test for Instrument Admissibility. UAI Tianjiao Chu, Richard Scheines, Peter Spirtes
2000	—	`book`	Causation, Prediction, and Search, Second Edition. Peter Spirtes, Clark Glymour, Richard Scheines
1997	A	`conf`	Estimating Latent Causal Inferences: Tetrad II model selection and Bayesian parameter estimation. AISTATS Richard Scheines
1994	J	`jnl`	Computer Environments for Proof Construction. Interact. Learn. Environ. Richard Scheines, Wilfried Sieg
1992	J	`jnl`	Finding latent variable models in large databases. Int. J. Intell. Syst. Richard Scheines, Peter Spirtes