Clark Glymour

Publication Activity (10 Years)

Years Active: 1972-2023
Publications (10 Years): 35

Top Topics

Causal Discovery

Measurement Error

Autism Spectrum Disorder

Top Venues

Publications

Feng Xie, Biwei Huang, Zhengming Chen, Ruichu Cai, Clark Glymour, Zhi Geng, Kun Zhang
Generalized Independent Noise Condition for Estimating Causal Structure with Latent Variables. CoRR (2023)
Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang
Latent Hierarchical Causal Structure Discovery with Rank Constraints. CoRR (2022)
Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
Action-Sufficient State Representation Learning for Control with Structural Constraints. ICML (2022)
Biwei Huang, Charles Jia Han Low, Feng Xie, Clark Glymour, Kun Zhang
Latent Hierarchical Causal Structure Discovery with Rank Constraints. NeurIPS (2022)
Wei Chen, Kun Zhang, Ruichu Cai, Biwei Huang, Joseph D. Ramsey, Zhifeng Hao, Clark Glymour
FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders. CoRR (2021)
Biwei Huang, Chaochao Lu, Liu Leqi, José Miguel Hernández-Lobato, Clark Glymour, Bernhard Schölkopf, Kun Zhang
Action-Sufficient State Representation Learning for Control with Structural Constraints. CoRR (2021)
Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Qingsong Liu, Clark Glymour
Domain Adaptation as a Problem of Inference on Graphical Models. NeurIPS (2020)
Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Clark Glymour
Domain Adaptation As a Problem of Inference on Graphical Models. CoRR (2020)
Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang
Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs. CoRR (2020)
Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour
Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets. AAAI (2020)
Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
Causal Discovery from Heterogeneous/Nonstationary Data. J. Mach. Learn. Res. 21 (2020)
Feng Xie, Ruichu Cai, Biwei Huang, Clark Glymour, Zhifeng Hao, Kun Zhang
Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs. NeurIPS (2020)
Biwei Huang, Kun Zhang, Ruben Sanchez-Romero, Joseph D. Ramsey, Madelyn Glymour, Clark Glymour
Diagnosis of Autism Spectrum Disorder by Causal Influence Strength Learned from Resting-State fMRI Data. CoRR (2019)
Biwei Huang, Kun Zhang, Jiji Zhang, Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
Causal Discovery from Heterogeneous/Nonstationary Data. CoRR (2019)
Biwei Huang, Kun Zhang, Pengtao Xie, Mingming Gong, Eric P. Xing, Clark Glymour
Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering. NeurIPS (2019)
Ruichu Cai, Feng Xie, Clark Glymour, Zhifeng Hao, Kun Zhang
Triad Constraints for Learning Causal Structure of Latent Variables. NeurIPS (2019)
Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models. CoRR (2019)
Biwei Huang, Kun Zhang, Mingming Gong, Clark Glymour
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models. ICML (2019)
Ruben Sanchez-Romero, Joseph D. Ramsey, Kun Zhang, Clark Glymour
Identification of Effective Connectivity Subregions. CoRR (2019)
Andrew J. Sedgewick, Kristina Buschur, Ivy Shi, Joseph D. Ramsey, Vineet K. Raghu, Dimitris V. Manatakis, Yingze Zhang, Jessica Bon, Divay Chandra, Chad Karoleski, Frank C. Sciurba, Peter Spirtes, Clark Glymour, Panayiotis V. Benos
Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis. Bioinform. 35 (7) (2019)
Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour
Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results. UAI (2018)
Mingming Gong, Kun Zhang, Biwei Huang, Clark Glymour, Dacheng Tao, Kayhan Batmanghelich
Causal Generative Domain Adaptation Networks. CoRR (2018)
Biwei Huang, Kun Zhang, Yizhu Lin, Bernhard Schölkopf, Clark Glymour
Generalized Score Functions for Causal Discovery. KDD (2018)
Vineet K. Raghu, Joseph D. Ramsey, Alison Morris, Dimitrios V. Manatakis, Peter Spirtes, Panos K. Chrysanthis, Clark Glymour, Panayiotis V. Benos
Comparison of strategies for scalable causal discovery of latent variable models from mixed data. Int. J. Data Sci. Anal. 6 (1) (2018)
Kun Zhang, Biwei Huang, Jiji Zhang, Clark Glymour, Bernhard Schölkopf
Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination. IJCAI (2017)
Andrew J. Sedgewick, Joseph D. Ramsey, Peter Spirtes, Clark Glymour, Panayiotis V. Benos
Mixed Graphical Models for Causal Analysis of Multi-modal Variables. CoRR (2017)
Mingming Gong, Kun Zhang, Bernhard Schölkopf, Clark Glymour, Dacheng Tao
Causal Discovery from Temporally Aggregated Time Series. UAI (2017)
Biwei Huang, Kun Zhang, Jiji Zhang, Ruben Sanchez-Romero, Clark Glymour, Bernhard Schölkopf
Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows. ICDM (2017)
Kun Zhang, Mingming Gong, Joseph D. Ramsey, Kayhan Batmanghelich, Peter Spirtes, Clark Glymour
Causal Discovery in the Presence of Measurement Error: Identifiability Conditions. CoRR (2017)
Joseph D. Ramsey, Madelyn Glymour, Ruben Sanchez-Romero, Clark Glymour
A million variables and more: the Fast Greedy Equivalence Search algorithm for learning high-dimensional graphical causal models, with an application to functional magnetic resonance images. Int. J. Data Sci. Anal. 3 (2) (2017)
Clark Glymour
Clark Glymour's responses to the contributions to the Synthese special issue "Causation, probability, and truth: the philosophy of Clark Glymour". Synth. 193 (4) (2016)
Kun Zhang, Jiji Zhang, Biwei Huang, Bernhard Schölkopf, Clark Glymour
On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection. UAI (2016)
Mingming Gong, Kun Zhang, Tongliang Liu, Dacheng Tao, Clark Glymour, Bernhard Schölkopf
Domain Adaptation with Conditional Transferable Components. ICML (2016)
Kenneth M. Ford, Patrick J. Hayes, Clark Glymour, James F. Allen
Cognitive Orthoses: Toward Human-Centered AI. AI Mag. 36 (4) (2015)
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
The center for causal discovery of biomedical knowledge from big data. J. Am. Medical Informatics Assoc. 22 (6) (2015)
Joseph D. Ramsey, Ruben Sanchez-Romero, Clark Glymour
Non-Gaussian methods and high-pass filters in the estimation of effective connections. NeuroImage 84 (2014)
Clark Glymour
Counterfactuals, graphical causal models and potential outcomes: Response to Lindquist and Sobel. NeuroImage 76 (2013)
Clark Glymour
Psychological and Normative Theories of Causal Power and the Probabilities of Causes CoRR (2013)
David Danks, Clark Glymour
Linearity Properties of Bayes Nets with Binary Variables CoRR (2013)
Catherine Hanson, Stephen José Hanson, Joseph D. Ramsey, Clark Glymour
Atypical Effective Connectivity of Social Brain Networks in Individuals with Autism. Brain Connect. 3 (6) (2013)
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 CoRR (2012)
Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
Learning Measurement Models for Unobserved Variables CoRR (2012)
Clark Glymour
On the Possibility of Inference to the Best Explanation. J. Philos. Log. 41 (2) (2012)
Joseph D. Ramsey, Stephen José Hanson, Clark Glymour
Multi-subject search correctly identifies causal connections and most causal directions in the DCM models of the Smith et al. simulation study. NeuroImage 58 (3) (2011)
Joseph D. Ramsey, Peter Spirtes, Clark Glymour
On meta-analyses of imaging data and the mixture of records. NeuroImage 57 (2) (2011)
Joseph D. Ramsey, Stephen José Hanson, Catherine Hanson, Yaroslav O. Halchenko, Russell A. Poldrack, Clark Glymour
Six problems for causal inference from fMRI. NeuroImage 49 (2) (2010)
Clark Glymour, David Danks, Bruce Glymour, Frederick Eberhardt, Joseph D. Ramsey, Richard Scheines, Peter Spirtes, Choh Man Teng, Jiji Zhang
Actual causation: a stone soup essay. Synth. 175 (2) (2010)
Carlos Perez, Eman El-Sheikh, Clark Glymour
Discovering effective connectivity among brain regions from functional MRI data. Int. J. Comput. Heal. 1 (1) (2010)
Eman El-Sheikh, Carlos Perez, Clark Glymour
Using Causal Modeling for Determining Connectivity among Brain Regions. IC-AI (2010)
Tianjiao Chu, Clark Glymour
Search for Additive Nonlinear Time Series Causal Models. J. Mach. Learn. Res. 9 (2008)
Robert E. Tillman, David Danks, Clark Glymour
Integrating Locally Learned Causal Structures with Overlapping Variables. NIPS (2008)
Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
Learning the Structure of Linear Latent Variable Models. J. Mach. Learn. Res. 7 (2006)
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)
Ricardo Bezerra de Andrade e Silva, Richard Scheines, Clark Glymour, Peter Spirtes
Learning Measurement Models for Unobserved Variables. UAI (2003)
Tianjiao Chu, Clark Glymour, Richard Scheines, Peter Spirtes
A Statistical Problem for Inference to Regulatory Structure from Associations of Gene Expression Measurements with Microarrays. Bioinform. 19 (9) (2003)
Jonathan Moody, Ricardo Bezerra de Andrade e Silva, Joseph Vanderwaart, Joseph D. Ramsey, Clark Glymour
Classification and filtering of spectra: A case study in mineralogy. Intell. Data Anal. 6 (6) (2002)
Joseph D. Ramsey, Paul Gazis, Ted Roush, Peter Spirtes, Clark Glymour
Automated Remote Sensing with Near Infrared Reflectance Spectra: Carbonate Recognition. Data Min. Knowl. Discov. 6 (3) (2002)
David Danks, Clark Glymour
Linearity Properties of Bayes Nets with Binary Variables. UAI (2001)
Clark Glymour
Android Epistemology For Babies: Relections On Words, Thoughts And Theories. Synth. 122 (1-2) (2000)
Clark Glymour
Rabbit Hunting. Synth. 121 (1-2) (1999)
Clark Glymour, Kenneth M. Ford, Patrick J. Hayes
Ramón Lull and the Infidels. AI Mag. 19 (2) (1998)
Clark Glymour
Buy and Use Thinking Things Through. Minds Mach. 8 (2) (1998)
Clark Glymour
Learning Causes: Psychological Explanations of Causal Explanation. Minds Mach. 8 (1) (1998)
Clark Glymour
Psychological and Normative Theories of Causal Power and the Probabilities of Causes. UAI (1998)
Gregory F. Cooper, Constantin F. Aliferis, Richard Ambrosino, John M. Aronis, Bruce G. Buchanan, Rich Caruana, Michael J. Fine, Clark Glymour, Geoffrey J. Gordon, Barbara H. Hanusa, Janine E. Janosky, Christopher Meek, Tom M. Mitchell, Thomas S. Richardson, Peter Spirtes
An evaluation of machine-learning methods for predicting pneumonia mortality. Artif. Intell. Medicine 9 (2) (1997)
Kenneth M. Ford, Clark Glymour, Patrick J. Hayes
On the Other Hand - Cognitive Prostheses. AI Mag. 18 (3) (1997)
Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth
Statistical Themes and Lessons for Data Mining. Data Min. Knowl. Discov. 1 (1) (1997)
Clark Glymour, David Madigan, Daryl Pregibon, Padhraic Smyth
Statistical Inference and Data Mining. Commun. ACM 39 (11) (1996)
Clark Glymour
Available Technology for Discovering Causal Models, Building Bayes Nets, and Selecting Predictors: The TETRAD II Program. KDD (1995)
Marek J. Druzdze, Clark Glymour
Application of the TETRAD II Program to the Study of Student Retention in U.S. Colleges. KDD Workshop (1994)
Kevin T. Kelly, Clark Glymour
Inductive inference from theory laden data. J. Philos. Log. 21 (4) (1992)
Clark Glymour
The hierarchies of knowledge and the mathematics of discovery. Minds Mach. 1 (1) (1991)
Kevin T. Kelly, Clark Glymour
Theory discovery from data with mixed quantifiers. J. Philos. Log. 19 (1) (1990)
Clark Glymour
Independence Assumptions and Bayesian Updating. Artif. Intell. 25 (1) (1985)
Clark Glymour, Richmond H. Thomason
Default Reasoning and the Logic of Theory Perturbation. NMR (1984)
Michael Friedman, Clark Glymour
If quanta had logic. J. Philos. Log. 1 (1) (1972)