Joseph D. Ramsey

Publication Activity (10 Years)

Years Active: 2002-2023
Publications (10 Years): 28

Top Topics

Latent Variables

Conditional Independence

Measurement Error

Causal Discovery

Top Venues

Int. J. Data Sci. Anal.

Publications

Bryan Andrews, Joseph D. Ramsey, Ruben Sanchez-Romero, Jazmin Camchong, Erich Kummerfeld
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow Shrink Trees. NeurIPS (2023)
Bryan Andrews, Joseph D. Ramsey, Ruben Sanchez-Romero, Jazmin Camchong, Erich Kummerfeld
Fast Scalable and Accurate Discovery of DAGs Using the Best Order Score Search and Grow-Shrink Trees. CoRR (2023)
Joseph D. Ramsey, Bryan Andrews
Py-Tetrad and RPy-Tetrad: A New Python Interface with R Support for Tetrad Causal Search. CAWS (2023)
Yujia Zheng, Biwei Huang, Wei Chen, Joseph D. Ramsey, Mingming Gong, Ruichu Cai, Shohei Shimizu, Peter Spirtes, Kun Zhang
Causal-learn: Causal Discovery in Python. CoRR (2023)
Joseph D. Ramsey, Bryan Andrews
Py-Tetrad and RPy-Tetrad: A New Python Interface with R Support for Tetrad Causal Search. CoRR (2023)
Wai-Yin Lam, Bryan Andrews, Joseph D. Ramsey
Greedy Relaxations of the Sparsest Permutation Algorithm. CoRR (2022)
Wai-Yin Lam, Bryan Andrews, Joseph D. Ramsey
Greedy relaxations of the sparsest permutation algorithm. UAI (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)
Joseph D. Ramsey
Improving Accuracy of Permutation DAG Search using Best Order Score Search. CoRR (2021)
Lujie Karen Chen, Joseph D. Ramsey, Artur Dubrawski
Affect, Support and Personal Factors: Multimodal Causal Models of One-on-one Coaching. EDM (2021)
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)
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)
Bryan Andrews, Joseph D. Ramsey, Gregory F. Cooper
Learning High-dimensional Directed Acyclic Graphs with Mixed Data-types. CD@KDD (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)
Joseph D. Ramsey, Bryan Andrews
FASK with Interventional Knowledge Recovers Edges from the Sachs Model. CoRR (2018)
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)
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)
Bryan Andrews, Joseph D. Ramsey, Gregory F. Cooper
Scoring Bayesian networks of mixed variables. Int. J. Data Sci. Anal. 6 (1) (2018)
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)
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)
Fattaneh Jabbari, Joseph D. Ramsey, Peter Spirtes, Gregory F. Cooper
Discovery of Causal Models that Contain Latent Variables Through Bayesian Scoring of Independence Constraints. ECML/PKDD (2) (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)
Joseph D. Ramsey, Bryan Andrews
A Comparison of Public Causal Search Packages on Linear, Gaussian Data with No Latent Variables. CoRR (2017)
Richard Scheines, Joseph D. Ramsey
Measurement Error and Causal Discovery. CFA@UAI (2016)
Erich Kummerfeld, Joseph D. Ramsey
Causal Clustering for 1-Factor Measurement Models. KDD (2016)
Joseph D. Ramsey
Improving Accuracy and Scalability of the PC Algorithm by Maximizing P-value. CoRR (2016)
Joseph D. Ramsey
Scaling up Greedy Equivalence Search for Continuous Variables. CoRR (2015)
Joseph D. Ramsey
Effects of Nonparanormal Transform on PC and GES Search Accuracies. CoRR (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)
Joseph D. Ramsey
A Scalable Conditional Independence Test for Nonlinear, Non-Gaussian Data. CoRR (2014)
Jeanette A. Mumford, Joseph D. Ramsey
Bayesian networks for fMRI: A primer. NeuroImage 86 (2014)
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)
Gustavo Lacerda, Peter Spirtes, Joseph D. Ramsey, Patrik O. Hoyer
Discovering Cyclic Causal Models by Independent Components Analysis CoRR (2012)
Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu
Causal discovery of linear acyclic models with arbitrary distributions CoRR (2012)
Joseph D. Ramsey, Jiji Zhang, Peter Spirtes
Adjacency-Faithfulness and Conservative Causal Inference. CoRR (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)
Stephen M. Smith, Karla L. Miller, Gholamreza Salimi Khorshidi, Matthew A. Webster, Christian F. Beckmann, Thomas E. Nichols, Joseph D. Ramsey, Mark William Woolrich
Network modelling methods for FMRI. NeuroImage 54 (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)
Gustavo Lacerda, Peter Spirtes, Joseph D. Ramsey, Patrik O. Hoyer
Discovering Cyclic Causal Models by Independent Components Analysis. UAI (2008)
Patrik O. Hoyer, Aapo Hyvärinen, Richard Scheines, Peter Spirtes, Joseph D. Ramsey, Gustavo Lacerda, Shohei Shimizu
Causal discovery of linear acyclic models with arbitrary distributions. UAI (2008)
Xue Bai, Rema Padman, Joseph D. Ramsey, Peter Spirtes
Tabu Search-Enhanced Graphical Models for Classification in High Dimensions. INFORMS J. Comput. 20 (3) (2008)
Joseph D. Ramsey, Jiji Zhang, Peter Spirtes
Adjacency-Faithfulness and Conservative Causal Inference. UAI (2006)
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)