Clark Glymour

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Searching the Heavens: Astronomy, Computation, Statistics, Data Mining and Philosophy

Clark Glymour, C. Glymour, 2012 .

N-1 Experiments Suffice to Determine the Causal Relations Among N Variables

Frederick Eberhardt, Richard Scheines, Clark Glymour, 2006 .

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

Clark Glymour, Joseph Ramsey, Madelyn Glymour, 2016, International Journal of Data Science and Analytics.

Default Reasoning and the Logic of Theory Perturbation

Richmond H. Thomason, Clark Glymour, C. Glymour, 1984, Non-Monotonic Reasoning.

Buy and Use Thinking Things Through

Clark Glymour, C. Glymour, 1998, Minds and Machines.

An evaluation of machine-learning methods for predicting pneumonia mortality

Constantin F. Aliferis, Tom M. Mitchell, Rich Caruana, 1997, Artif. Intell. Medicine.

Android epistemology

Kenneth M. Ford, Patrick J. Hayes, Clark Glymour, 1995 .

Using Artificial Intelligence to Aid in the Development of Causal Models

Richard Scheines, Clark Glymour, Peter Spirtes, 1990 .

Specific and Shared Causal Relation Modeling and Mechanism-Based Clustering

Pengtao Xie, Eric P. Xing, Kun Zhang, 2019, NeurIPS.

Artificial Intelligence for Statistical and Causal Modelling

Clark Glymour, C. Glymour, 1988 .

Learning Measurement Models for Unobserved Variables

Richard Scheines, Clark Glymour, Ricardo Bezerra de Andrade e Silva, 2002, UAI.

Ramon Lull and the Infidels

Kenneth M. Ford, Patrick J. Hayes, Clark Glymour, 1998 .

Identification of Effective Connectivity Subregions pdf

Clark Glymour, Ruben Sanchez-Romero, Kun Zhang, 2019, ArXiv.

Linearity Properties of Bayes Nets with Binary Variables

David Danks, Clark Glymour, C. Glymour, 2001, UAI.

Learning causality and causality-related learning: some recent progress.

Bernhard Schölkopf, Clark Glymour, Kun Zhang, 2018, National science review.

Generalized Independent Noise Condition for Estimating Linear Non-Gaussian Latent Variable Graphs pdf

Ruichu Cai, Clark Glymour, Zhifeng Hao, 2020, ArXiv.

Why the University Should Abolish Faculty Course Evaluations

Clark Glymour, 2003 .

Comparison of strategies for scalable causal discovery of latent variable models from mixed data

Panos K. Chrysanthis, Clark Glymour, Joseph Ramsey, 2018, International Journal of Data Science and Analytics.

Statistical inference and data mining

Padhraic Smyth, Clark Glymour, David Madigan, 1996, CACM.

Simulation Studies of the Reliability of Computer-Aided Model Specification Using the TETRAD II, EQS, and LISREL Programs

Richard Scheines, Clark Glymour, Peter Spirtes, 1990 .

Thoroughly Modern Meno

Kevin T. Kelly, Clark Glymour, C. Glymour, 1988 .

On-board Science Understanding: NASA Ames' Efforts

Virginia C. Gulick, Peter Cheeseman, Clark Glymour, 1998 .

The center for causal discovery of biomedical knowledge from big data

Richard Scheines, Gregory F. Cooper, Clark Glymour, 2015, J. Am. Medical Informatics Assoc..

Discovering Causal Structure: Artificial Intelligence, Philosophy of Science, and Statistical Modeling

Richard Scheines, Kevin T. Kelly, Clark Glymour, 1987 .

Problems for Structure Learning Aggregation and Computational Complexity

David Danks, Clark Glymour, Tianjiao Chu, 2009 .

Inductive inference from theory laden data

Kevin T. Kelly, Clark Glymour, C. Glymour, 1992, J. Philos. Log..

What Do College Ranking Data Tell Us About Student Retention

Marek J. Druzdzel, Clark Glymour, Marek J Druzdzel, 1994 .

Classification and filtering of spectra: A case study in mineralogy

Clark Glymour, Ricardo Bezerra de Andrade e Silva, Joseph Vanderwaart, 2002, Intell. Data Anal..

Six problems for causal inference from fMRI

Russell A. Poldrack, Clark Glymour, Yaroslav O. Halchenko, 2010, NeuroImage.

Causal Discovery

Clark Glymour, 2010, Encyclopedia of Machine Learning.

On the Possibility of Inference to the Best Explanation

Clark Glymour, 2012, J. Philos. Log..

Rabbit Hunting

Clark Glymour, C. Glymour, 2004, Synthese.

On the Other Hand - Cognitive Prostheses

Kenneth M. Ford, Patrick J. Hayes, Clark Glymour, 1997, AI Mag..

Development of Intelligent, Computerized Aids for the Specification of Casual Models from Large Data Bases

Richard Scheines, Clark Glymour, Peter Spirtes, 1992 .

Causal Discovery from Non-Identical Variable Sets

Clark Glymour, Mingming Gong, Biwei Huang, 2020, AAAI 2020.

Hans Reichenbach's Probability Logic

Frederick Eberhardt, Clark Glymour, C. Glymour, 2011, Inductive Logic.

Atypical Effective Connectivity of Social Brain Networks in Individuals with Autism

Clark Glymour, Stephen Jose Hanson, Catherine Hanson, 2013, Brain Connect..

Learning the Structure of Deterministic Systems

Clark Glymour, C. Glymour, 2007 .

Learning the Structure of Linear Latent Variable Models

Richard Scheines, Clark Glymour, Ricardo Bezerra de Andrade e Silva, 2006, J. Mach. Learn. Res..

On meta-analyses of imaging data and the mixture of records

Clark Glymour, Joseph Ramsey, Peter Spirtes, 2011, NeuroImage.

Causal Discovery from Heterogeneous/Nonstationary Data pdf

Bernhard Schölkopf, Kun Zhang, Clark Glymour, 2019, J. Mach. Learn. Res..

Exploring Causal Structure with the TETRAD Program

Richard Scheines, Clark Glymour, Peter Spirtes, 1988 .

Multi-subject search correctly identifies causal connections and most causal directions in the DCM models of the Smith et al. simulation study

Clark Glymour, Joseph Ramsey, Stephen Jose Hanson, 2011, NeuroImage.

Identification of Mechanisms of Functional Signaling Between Human Hippocampus Regions

Clark Glymour, Ruben Sanchez-Romero, Joseph Ramsey, 2017, bioRxiv.

Search for Additive Nonlinear Time Series Causal Models

Clark Glymour, Tianjiao Chu, C. Glymour, 2008, J. Mach. Learn. Res..

Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results

Kun Zhang, Mingming Gong, Clark Glymour, 2018, UAI.

Using Causal Modeling for Determining Connectivity among Brain Regions

Carlos Perez, Clark Glymour, Eman El-Sheikh, 2010, IC-AI.

A qualitative approach to causal modeling

Richard Scheines, Clark Glymour, Peter Spirtes, 1991 .

Discovery and Visualization of Nonstationary Causal Models

Kun Zhang, Clark Glymour, Jiji Zhang, 2015, 1509.08056.

On Causal Discovery in the Presence of Changing Causal Models

Kun Zhang, Clark Glymour, Jiji Zhang, 2015 .

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

Richard Scheines, Clark Glymour, Peter Spirtes, 2003, Bioinform..

Constructing Bayesian Network Models of Gene Expression Networks from Microarray Data

Richard Scheines, Clark Glymour, Stuart Kauffman, 2000 .

Causal Discovery from Heterogeneous/Nonstationary Data with Independent Changes.

Clark Glymour, Jiji Zhang, Bernhard Scholkopf, 2019 .

Foundations of Space Time Theories

Clark Glymour, John Earman, John J. Stachel, 1977 .

Having the Right Tool: Causal Graphs in Teaching Research Design

Marek J. Druzdzel, Clark Glymour, 1995 .

Diagnosis of Autism Spectrum Disorder by Causal Influence Strength Learned from Resting-State fMRI Data pdf

Clark Glymour, Kun Zhang, Joseph Ramsey, 2019, ArXiv.

The Evaluation of Discovery: Models, Simulation and Search through “Big Data”

Clark Glymour, Kun Zhang, Joseph Ramsey, 2019, Open Philosophy.

Tetrad II: User's Manual

Richard Scheines, Christopher Meek, Clark Glymour, 1994 .

THE PROBLEMS OF SCIENCE WITHOUT EXPERIMENTS

Richard Scheines, Kevin T. Kelly, Clark Glymour, 1987 .

Cognitive Orthoses: Toward Human-Centered AI

Kenneth M. Ford, Patrick J. Hayes, James F. Allen, 2015, AI Mag..

Inferring causation from time series in Earth system sciences

Bernhard Schölkopf, Marten Scheffer, Markus Reichstein, 2019, Nature Communications.

Causal Discovery of Feedback Networks with Functional Magnetic Resonance Imaging

Kun Zhang, Clark Glymour, Joseph Ramsey, 2018, bioRxiv.

Counterfactuals, graphical causal models and potential outcomes: Response to Lindquist and Sobel

Clark Glymour, C. Glymour, 2013, NeuroImage.

If quanta had logic

Clark Glymour, Michael Friedman, 1972, J. Philos. Log..

Revisions of Bootstrap Testing

Clark Glymour, 1983, Philosophy of Science.

Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models

Kun Zhang, Clark Glymour, Biwei Huang, 2019, ICML.

The Computational and Experimental Complexity of Gene Perturbations for Regulatory Network Search

David Danks, Clark Glymour, Peter Spirtes, 2003 .

Learning Causes: Psychological Explanations of Causal Explanation1

Clark Glymour, C. Glymour, 1998, Minds and Machines.

Convergence to the Truth and Nothing but the Truth

Kevin T. Kelly, Clark Glymour, 1989, Philosophy of Science.

Causation, Prediction, and Search, Second Edition

Richard Scheines, Clark Glymour, Peter Spirtes, 2000, Adaptive computation and machine learning.

Behind Distribution Shift: Mining Driving Forces of Changes and Causal Arrows

Bernhard Schölkopf, Clark Glymour, Jiji Zhang, 2017, 2017 IEEE International Conference on Data Mining (ICDM).

Statistical Themes and Lessons for Data Mining

Padhraic Smyth, Clark Glymour, David Madigan, 2004, Data Mining and Knowledge Discovery.

Generalized Independent Noise Condition for Estimating Latent Variable Causal Graphs

Ruichu Cai, Clark Glymour, Zhifeng Hao, 2020, NeurIPS.

Inferring causal structure in mixed populations

Richard Scheines, Clark Glymour, P. Spirtes, 1993 .

On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection

Bernhard Schölkopf, Clark Glymour, Kun Zhang, 2016, UAI.

Automated Remote Sensing with Near Infrared Reflectance Spectra: Carbonate Recognition

Clark Glymour, Joseph Ramsey, Peter Spirtes, 2002, Data Mining and Knowledge Discovery.

The hierarchies of knowledge and the mathematics of discovery

Clark Glymour, 2004, Minds and Machines.

Statistical inference and data mining : Data mining and knowledge discovery in databases

Padhraic Smyth, Clark Glymour, David Madigan, 1996 .

A Fast Algorithm for Discovering Sparse Causal Graphs

Clark Glymour, Peter Spirtes, P. Spirtes, 1991 .

Inductive inference in the limit

Clark Glymour, 1985 .

12 – RUNNING TETRAD

Richard Scheines, Kevin T. Kelly, Clark Glymour, 1987 .

Why you'll never know whether Roger Penrose is a computer

Kevin T. Kelly, Clark Glymour, C. Glymour, 1990, Behavioral and Brain Sciences.

Automated Target Detection and Grouping From Remotely Sensed Data

Choh Man Teng, Clark Glymour, Brian Bonnlander, 2006 .

Generalized Score Functions for Causal Discovery

Bernhard Schölkopf, Clark Glymour, Kun Zhang, 2018, KDD.

Causal Discovery from Multiple Data Sets with Non-Identical Variable Sets

Kun Zhang, Clark Glymour, Mingming Gong, 2020, AAAI.

Truth is among the best explanations: Finding causal explanations of conditional independence and dependence

Richard Scheines, Christopher Meek, Clark Glymour, 1999 .

Actual causation: a stone soup essay

Choh Man Teng, Frederick Eberhardt, Richard Scheines, 2009, Synthese.

Thinking about Android Epistemology (AAAI Press Copublications)

Kenneth M. Ford, Patrick J. Hayes, Clark Glymour, 2006, AAAI 2006.

Causal modeling with the TETRAD program

Richard Scheines, Clark Glymour, C. Glymour, 1986, Synthese.

Non-Gaussian methods and high-pass filters in the estimation of effective connections

Clark Glymour, Ruben Sanchez-Romero, Joseph Ramsey, 2014, NeuroImage.

Available Technology for Discovering Causal Models, Building Bayes Nets, and Selecting Predictors: The TETRAD II Program

Clark Glymour, 1995, KDD.

Theory discovery from data with mixed quantifiers

Kevin T. Kelly, Clark Glymour, 1990, J. Philos. Log..

TETRAD: Discovering Causal Structure.

Richard Scheines, Clark Glymour, Peter Spirtes, 1988, Multivariate behavioral research.

Android Epistemology For Babies: Relections On Words, Thoughts And Theories

Clark Glymour, 2004, Synthese.

Human-System Technology: Human-Robot Interaction to Address Critical Navy Needs of the Present and Future

Jeffrey M. Bradshaw, Clark Glymour, Jerry Pratt, 2006 .

Psychological and Normative Theories of Causal Power and the Probabilities of Causes

Clark Glymour, C. Glymour, 1998, UAI.

TETRAD II : tools for causal modeling

Richard Scheines, Christopher Meek, Clark Glymour, 1994 .

Causal Discovery from Nonstationary/Heterogeneous Data: Skeleton Estimation and Orientation Determination

Bernhard Schölkopf, Clark Glymour, Kun Zhang, 2017, IJCAI.

Regression, Causation and Prediction

Richard Scheines, Clark Glymour, Peter Spirtes, 1993 .

The automation of discovery

Clark Glymour, C. Glymour, 2004, Daedalus.

What Revisions Does Bootstrap Testing Need

Clark Glymour, John Earman, C. Glymour, 1988 .

Why I am not a Bayesian

Clark Glymour, C. Glymour, 2016 .

Reverse Inference in Neuropsychology

Clark Glymour, Catherine Hanson, C. Glymour, 2016, The British Journal for the Philosophy of Science.

Domain Adaptation with Conditional Transferable Components

Bernhard Schölkopf, Dacheng Tao, Mingming Gong, 2016, ICML.

Topology, Cosmology and Convention

Clark Glymour, 1972 .

8 – CASE STUDIES

Richard Scheines, Kevin T. Kelly, Clark Glymour, 1987 .

Discovery Algorithms for Causally Sufficient Structures

Richard Scheines, Clark Glymour, Peter Spirtes, 1993 .

Clark Glymour’s responses to the contributions to the Synthese special issue “Causation, probability, and truth: the philosophy of Clark Glymour”

Clark Glymour, 2016, Synthese.

Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis

Clark Glymour, Dimitris V. Manatakis, Joseph Ramsey, 2018, Bioinform..

TETRAD II: Tools for Discovery

Richard Scheines, Christopher Meek, Clark Glymour, 1994 .

Estimating feedforward and feedback effective connections from fMRI time series: Assessments of statistical methods

Clark Glymour, Ruben Sanchez-Romero, Biwei Huang, 2019, Network Neuroscience.

Triad Constraints for Learning Causal Structure of Latent Variables

Ruichu Cai, Clark Glymour, Feng Xie, 2019, NeurIPS.

Ramón Lull and the Infidels

Kenneth M. Ford, Patrick J. Hayes, Clark Glymour, 1998, AI Mag..

Building Latent Variable Models

Richard Scheines, Clark Glymour, Peter Spirtes, 1991 .

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

Frederick Eberhardt, Richard Scheines, Clark Glymour, 2005, UAI.

Bootstraps and Probabilities

Clark Glymour, C. Glymour, 1980 .

Artificial Intelligence is Philosophy

Clark Glymour, 1988 .

Causal Generative Domain Adaptation Networks pdf

Dacheng Tao, Mingming Gong, Clark Glymour, 2018, ArXiv.

Elaborating Linear Theories with Unmeasured Variables

Richard Scheines, Clark Glymour, Peter Spirtes, 1993 .

Causal Discovery from Temporally Aggregated Time Series

Bernhard Schölkopf, Dacheng Tao, Mingming Gong, 2017, UAI.

Application of the TETRAD II Program to the Study of Student Retention in U.S. Colleges

Clark Glymour, Marek J. Druzdze, 1994, KDD Workshop.

7 – SIMULATION STUDIES

Richard Scheines, Kevin T. Kelly, Clark Glymour, 1987 .

Discovering effective connectivity among brain regions from functional MRI data

Carlos Perez, Clark Glymour, Eman El-Sheikh, 2010, Int. J. Comput. Heal..

The expected complexity of problem solving

Kevin T. Kelly, Clark Glymour, Peter Spirtes, 1987 .

Domain Adaptation As a Problem of Inference on Graphical Models pdf

Kun Zhang, Petar Stojanov, Clark Glymour, 2020, NeurIPS.

Confirmation And Chaos*

Clark Glymour, Maralee Harrell, C. Glymour, 2002, Philosophy of Science.

OBJECTIONS TO DISCOVERY BY COMPUTER

Richard Scheines, Kevin T. Kelly, Clark Glymour, 1987 .

JON WILLIAMSON Bayesian Nets and Causality

Clark Glymour, C. Glymour, 2009, The British Journal for the Philosophy of Science.

Independence Assumptions and Bayesian Updating

Clark Glymour, C. Glymour, 1985, Artif. Intell..

Comorbid science? 1

Richard Scheines, David Danks, Clark Glymour, 2010, Behavioral and Brain Sciences.

Causal Discovery in the Presence of Measurement Error: Identifiability Conditions pdf

Mingming Gong, Clark Glymour, Kun Zhang, 2017, ArXiv.

Integrating Locally Learned Causal Structures with Overlapping Variables

David Danks, Clark Glymour, Robert E. Tillman, 2008, NIPS.

Automated Search for Causal Relations: Theory and Practice

Richard Scheines, Clark Glymour, Peter Spirtes, 2010 .

Mixed Graphical Models for Causal Analysis of Multi-modal Variables pdf

Clark Glymour, Joseph Ramsey, Andrew J. Sedgewick, 2017, ArXiv.

Why Probability Does Not Capture the Logic of Scientific Justification

Kevin T. Kelly, Clark Glymour, C. Glymour, 2004 .

Action-Sufficient State Representation Learning for Control with Structural Constraints pdf

Jos'e Miguel Hern'andez-Lobato, Clark Glymour, Bernhard Scholkopf, 2021, ArXiv.

FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders pdf

Ruichu Cai, Clark Glymour, Zhifeng Hao, 2021, ArXiv.

Searching the DCM Model Space, and Some Generalizations

Clark Glymour, C. Glymour, Michael Freenor, 2010 .

Discovery Algorithms without Causal Sufficiency

Richard Scheines, Clark Glymour, Peter Spirtes, 1993 .

CAUSAL AND STATISTICAL MODELS

Richard Scheines, Kevin T. Kelly, Clark Glymour, 1987 .

On the Methods of Cognitive Neuropsychology

Clark Glymour, C. Glymour, 1994, The British Journal for the Philosophy of Science.

Autonomous Science Decision Making for Mars Sample Return

Virginia C. Gulick, Clark Glymour, Wray Buntine, 1999 .

Inductive inference in the limit

Clark Glymour, C. Glymour, 1985 .

The prehistory of android epistemology

Kenneth M. Ford, Patrick J. Hayes, Clark Glymour, 1995 .

Social Statistics and Genuine Inquiry: Reflections on The Bell Curve

Clark Glymour, C. Glymour, 1997 .

What Went Wrong? Reflections on Science by Observation and the Bell Curve

Clark Glymour, C. Glymour, 1998, Philosophy of Science.

Review: Cause and Chance: Causation in an Indeterministic World

Clark Glymour, 2005 .

The Concept of Probability in the Mathematical Representation of Reality

Frederick Eberhardt, Clark Glymour, Hans Reichenbach, 2008 .

We believe in freedom of the will so that we can learn

Clark Glymour, 2004, Behavioral and Brain Sciences.

Conceptual scheming or confessions of a metaphysical realist

Clark Glymour, 2004, Synthese.

Experiments on the Accuracy of Algorithms for Inferring the Structure of Genetic Regulatory Networks from Microarray Expression Levels

Clark Glymour, Joseph Ramsey, Thomas Heiman, 2003 .

PCX : Markov Blanket Classification for Large Data Sets with Few Cases

Rema Padman, Clark Glymour, Joseph Ramsey, 2004 .

The Tetrad Project

Richard Scheines, Clark Glymour, Peter Spirtes, 1990 .

Reichenbach's entanglements

Clark Glymour, 2004, Synthese.

Causation and Prediction: Axioms and Explications

Richard Scheines, Clark Glymour, Peter Spirtes, 1993 .

On Some Patterns of Reduction

Clark Glymour, C. Glymour, 1970, Philosophy of Science.

James Woodward, Making Things Happen: A Theory of Causal Explanation, Oxford, 2003, 418pp, $65.00 (hbk) ISBN 0195155270

Clark Glymour, C. Glymour, 2004 .

Discussion of Causal Diagrams for Empirical Research by J. Pearl

Stephen E. Fienberg, Clark Glymour, Peter Spirtes, 1995 .

Actual Causes and Thought Experiments

Clark Glymour, Frank Wimberly, 2003 .

The Structure of the Unobserved

Richard Scheines, Clark Glymour, Peter Spirtes, 1993 .

Autonomous Science Decisions for Mars Sample Return

Virginia C. Gulick, Clark Glymour, Wray Buntine, 1999 .

Theoretical Realism and Theoretical Equivalence

Clark Glymour, C. Glymour, 1970, PSA: Proceedings of the Biennial Meeting of the Philosophy of Science Association.

Review of James Woodward, Making Things Happen: A Theory of Causal Explanation

Clark Glymour, C. Glymour, 2004 .

Reichenbach’s Entanglements

Clark Glymour, C. Glymour, 1977 .

Thinking about android epistemology

Kenneth M. Ford, Patrick J. Hayes, Clark Glymour, 2006 .

Hypothetico-Deductivism Is Hopeless

Clark Glymour, C. Glymour, 1980, Philosophy of Science.

Evidence of systematic expressed sequence tag IMAGE clone cross-hybridization on cDNA microarrays.

Larry Wasserman, Richard Scheines, Clark Glymour, 2004, Genomics.

Introduction and Advertisement

Richard Scheines, Clark Glymour, Peter Spirtes, 1993 .