Automated Remote Sensing with Near Infrared Reflectance Spectra: Carbonate Recognition. - Joseph D. Ramsey; Paul Gazis; Ted Roush; Peter Spirtes; Clark Glymour (Data Min. Knowl. Discov., 2002)

Classification and filtering of spectra: A case study in mineralogy. - Jonathan Moody; Ricardo Bezerra de Andrade e Silva; Joseph Vanderwaart; Joseph D. Ramsey; Clark Glymour (Intell. Data Anal., 2002)

Adjacency-Faithfulness and Conservative Causal Inference. - Joseph D. Ramsey; Jiji Zhang; Peter Spirtes (UAI, 2006)

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)

Discovering Cyclic Causal Models by Independent Components Analysis. - Gustavo Lacerda; Peter Spirtes; Joseph D. Ramsey; Patrik O. Hoyer (UAI, 2008)

Tabu Search-Enhanced Graphical Models for Classification in High Dimensions. - Xue Bai; Rema Padman; Joseph D. Ramsey; Peter Spirtes (INFORMS J. Comput., 2008)

Six problems for causal inference from fMRI. - Joseph D. Ramsey; Stephen José Hanson; Catherine Hanson; Yaroslav O. Halchenko; Russell A. Poldrack; Clark Glymour (NeuroImage, 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)

Multi-subject search correctly identifies causal connections and most causal directions in the DCM models of the Smith et al. simulation study. - Joseph D. Ramsey; Stephen José Hanson; Clark Glymour (NeuroImage, 2011)

On meta-analyses of imaging data and the mixture of records. - Joseph D. Ramsey; Peter Spirtes; Clark Glymour (NeuroImage, 2011)

Network modelling methods for FMRI. - Stephen M. Smith 001; Karla L. Miller; Gholamreza Salimi Khorshidi; Matthew A. Webster; Christian F. Beckmann; Thomas E. Nichols; Joseph D. Ramsey; Mark William Woolrich (NeuroImage, 2011)

Atypical Effective Connectivity of Social Brain Networks in Individuals with Autism. - Catherine Hanson; Stephen José Hanson; Joseph D. Ramsey; Clark Glymour (Brain Connect., 2013)

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

A Scalable Conditional Independence Test for Nonlinear, Non-Gaussian Data. - Joseph D. Ramsey (CoRR, 2014)

Bayesian networks for fMRI: A primer. - Jeanette A. Mumford; Joseph D. Ramsey (NeuroImage, 2014)

Non-Gaussian methods and high-pass filters in the estimation of effective connections. - Joseph D. Ramsey; Ruben Sanchez-Romero; Clark Glymour (NeuroImage, 2014)

Effects of Nonparanormal Transform on PC and GES Search Accuracies. - Joseph D. Ramsey (CoRR, 2015)

Scaling up Greedy Equivalence Search for Continuous Variables. - Joseph D. Ramsey (CoRR, 2015)

Causal Clustering for 1-Factor Measurement Models. - Erich Kummerfeld; Joseph D. Ramsey (KDD, 2016)

A Hybrid Causal Search Algorithm for Latent Variable Models. - Juan Miguel Ogarrio; Peter Spirtes; Joe Ramsey (Probabilistic Graphical Models, 2016)

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

Improving Accuracy and Scalability of the PC Algorithm by Maximizing P-value. - Joseph D. Ramsey (CoRR, 2016)

Discovery of Causal Models that Contain Latent Variables Through Bayesian Scoring of Independence Constraints. - Fattaneh Jabbari; Joseph D. Ramsey; Peter Spirtes; Gregory F. Cooper (ECML/PKDD (2), 2017)

Mixed Graphical Models for Causal Analysis of Multi-modal Variables. - Andrew J. Sedgewick; Joseph D. Ramsey; Peter Spirtes; Clark Glymour; Panayiotis V. Benos (CoRR, 2017)

Causal Discovery in the Presence of Measurement Error: Identifiability Conditions. - Kun Zhang 001; Mingming Gong; Joseph D. Ramsey; Kayhan Batmanghelich; Peter Spirtes; Clark Glymour (CoRR, 2017)

A Comparison of Public Causal Search Packages on Linear, Gaussian Data with No Latent Variables. - Joseph D. Ramsey; Bryan Andrews (CoRR, 2017)

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. - Joseph D. Ramsey; Madelyn Glymour; Ruben Sanchez-Romero; Clark Glymour (Int. J. Data Sci. Anal., 2017)

Causal Discovery with Linear Non-Gaussian Models under Measurement Error: Structural Identifiability Results. - Kun Zhang 001; Mingming Gong; Joseph D. Ramsey; Kayhan Batmanghelich; Peter Spirtes; Clark Glymour (UAI, 2018)

FASK with Interventional Knowledge Recovers Edges from the Sachs Model. - Joseph D. Ramsey; Bryan Andrews (CoRR, 2018)

Scoring Bayesian networks of mixed variables. - Bryan Andrews; Joseph D. Ramsey; Gregory F. Cooper (Int. J. Data Sci. Anal., 2018)

Comparison of strategies for scalable causal discovery of latent variable models from mixed data. - Vineet K. Raghu; Joseph D. Ramsey; Alison Morris; Dimitrios V. Manatakis; Peter Spirtes; Panos K. Chrysanthis; Clark Glymour; Panayiotis V. Benos (Int. J. Data Sci. Anal., 2018)

Learning High-dimensional Directed Acyclic Graphs with Mixed Data-types. - Bryan Andrews; Joseph D. Ramsey; Gregory F. Cooper (CD@KDD, 2019)

Mixed graphical models for integrative causal analysis with application to chronic lung disease diagnosis and prognosis. - 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; et al. (Bioinform., 2019)

Diagnosis of Autism Spectrum Disorder by Causal Influence Strength Learned from Resting-State fMRI Data. - Biwei Huang; Kun Zhang 001; Ruben Sanchez-Romero; Joseph D. Ramsey; Madelyn Glymour; Clark Glymour (CoRR, 2019)

Identification of Effective Connectivity Subregions. - Ruben Sanchez-Romero; Joseph D. Ramsey; Kun Zhang 001; Clark Glymour (CoRR, 2019)

Causal Discovery from Heterogeneous/Nonstationary Data. - Biwei Huang; Kun Zhang 001; Jiji Zhang; Joseph D. Ramsey; Ruben Sanchez-Romero; Clark Glymour; Bernhard Schölkopf (J. Mach. Learn. Res., 2020)

Affect, Support and Personal Factors: Multimodal Causal Models of One-on-one Coaching. - Lujie Karen Chen; Joseph D. Ramsey; Artur Dubrawski (EDM, 2021)

FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders. - Wei Chen 103; Kun Zhang 001; Ruichu Cai; Biwei Huang; Joseph D. Ramsey; Zhifeng Hao; Clark Glymour (CoRR, 2021)

Improving Accuracy of Permutation DAG Search using Best Order Score Search. - Joseph D. Ramsey (CoRR, 2021)

Greedy relaxations of the sparsest permutation algorithm. - Wai-Yin Lam; Bryan Andrews; Joseph D. Ramsey (UAI, 2022)

Py-Tetrad and RPy-Tetrad: A New Python Interface with R Support for Tetrad Causal Search. - Joseph D. Ramsey; Bryan Andrews (CAWS, 2023)

Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow Shrink Trees. - Bryan Andrews; Joseph D. Ramsey; Ruben Sanchez-Romero; Jazmin Camchong; Erich Kummerfeld (NeurIPS, 2023)

Choosing DAG Models Using Markov and Minimal Edge Count in the Absence of Ground Truth. - Joseph D. Ramsey; Bryan Andrews; Peter Spirtes (CoRR, 2024)

Causal-learn: Causal Discovery in Python. - Yujia Zheng 001; Biwei Huang; Wei Chen 103; Joseph D. Ramsey; Mingming Gong; Ruichu Cai; Shohei Shimizu; Peter Spirtes; Kun Zhang 001 (J. Mach. Learn. Res., 2024)

Selecting Accurate Subgraphical Models from Possibly Inaccurate Graphical Models. - Yi Han; Joseph D. Ramsey; Peter Spirtes (CLeaR, 2025)