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Items: 36

1.

Review of Causal Discovery Methods Based on Graphical Models.

Glymour C, Zhang K, Spirtes P.

Front Genet. 2019 Jun 4;10:524. doi: 10.3389/fgene.2019.00524. eCollection 2019. Review.

2.

Inferring causation from time series in Earth system sciences.

Runge J, Bathiany S, Bollt E, Camps-Valls G, Coumou D, Deyle E, Glymour C, Kretschmer M, Mahecha MD, Muñoz-Marí J, van Nes EH, Peters J, Quax R, Reichstein M, Scheffer M, Schölkopf B, Spirtes P, Sugihara G, Sun J, Zhang K, Zscheischler J.

Nat Commun. 2019 Jun 14;10(1):2553. doi: 10.1038/s41467-019-10105-3. Review.

3.

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

Sanchez-Romero R, Ramsey JD, Zhang K, Glymour MRK, Huang B, Glymour C.

Netw Neurosci. 2019 Feb 1;3(2):274-306. doi: 10.1162/netn_a_00061. eCollection 2019.

4.

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

Sedgewick AJ, Buschur K, Shi I, Ramsey JD, Raghu VK, Manatakis DV, Zhang Y, Bon J, Chandra D, Karoleski C, Sciurba FC, Spirtes P, Glymour C, Benos PV.

Bioinformatics. 2019 Apr 1;35(7):1204-1212. doi: 10.1093/bioinformatics/bty769.

PMID:
30192904
5.

Generalized Score Functions for Causal Discovery.

Huang B, Zhang K, Lin Y, Schölkopf B, Glymour C.

KDD. 2018 Aug;2018:1551-1560. doi: 10.1145/3219819.3220104.

6.

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

Raghu VK, Ramsey JD, Morris A, Manatakis DV, Sprites P, Chrysanthis PK, Glymour C, Benos PV.

Int J Data Sci Anal. 2018;6(1):33-45. doi: 10.1007/s41060-018-0104-3. Epub 2018 Feb 6.

7.

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

Zhang K, Schölkopf B, Spirtes P, Glymour C.

Natl Sci Rev. 2018 Jan;5(1):26-29. doi: 10.1093/nsr/nwx137. Epub 2017 Nov 17. No abstract available.

8.

Causal Discovery from Temporally Aggregated Time Series.

Gong M, Zhang K, Schölkopf B, Glymour C, Tao D.

Uncertain Artif Intell. 2017 Aug;2017. pii: 269.

9.

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

Huang B, Zhang K, Zhang J, Sanchez-Romero R, Glymour C, Schölkopf B.

Proc IEEE Int Conf Data Min. 2017 Nov;2017:913-918. doi: 10.1109/ICDM.2017.114. Epub 2017 Dec 18.

10.

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

Zhang K, Huang B, Zhang J, Glymour C, Schölkopf B.

IJCAI (U S). 2017 Aug;2017:1347-1353. doi: 10.24963/ijcai.2017/187.

11.

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.

Ramsey J, Glymour M, Sanchez-Romero R, Glymour C.

Int J Data Sci Anal. 2017 Mar;3(2):121-129. doi: 10.1007/s41060-016-0032-z. Epub 2016 Dec 1.

12.

Domain Adaptation with Conditional Transferable Components.

Gong M, Zhang K, Liu T, Tao D, Glymour C, Schölkopf B.

JMLR Workshop Conf Proc. 2016 Jun;48:2839-2848.

13.

What Is Going on Inside the Arrows? Discovering the Hidden Springs in Causal Models.

Murray-Watters A, Glymour C.

Philos Sci. 2015 Oct;82(4):556-586.

14.

The center for causal discovery of biomedical knowledge from big data.

Cooper GF, Bahar I, Becich MJ, Benos PV, Berg J, Espino JU, Glymour C, Jacobson RC, Kienholz M, Lee AV, Lu X, Scheines R; Center for Causal Discovery team.

J Am Med Inform Assoc. 2015 Nov;22(6):1132-6. doi: 10.1093/jamia/ocv059. Epub 2015 Jul 2.

15.

Commentary: race and sex are causes.

Glymour C, Glymour MR.

Epidemiology. 2014 Jul;25(4):488-90. doi: 10.1097/EDE.0000000000000122. No abstract available.

PMID:
24887161
16.

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

Ramsey JD, Sanchez-Romero R, Glymour C.

Neuroimage. 2014 Jan 1;84:986-1006. doi: 10.1016/j.neuroimage.2013.09.062. Epub 2013 Oct 5.

PMID:
24099845
17.

Atypical effective connectivity of social brain networks in individuals with autism.

Hanson C, Hanson SJ, Ramsey J, Glymour C.

Brain Connect. 2013;3(6):578-89. doi: 10.1089/brain.2013.0161. Epub 2013 Nov 12.

PMID:
24093627
18.

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

Glymour C.

Neuroimage. 2013 Aug 1;76:450-1. doi: 10.1016/j.neuroimage.2011.07.071. Epub 2011 Jul 30.

PMID:
21835247
19.

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

Ramsey JD, Hanson SJ, Glymour C.

Neuroimage. 2011 Oct 1;58(3):838-48. doi: 10.1016/j.neuroimage.2011.06.068. Epub 2011 Jul 1.

PMID:
21745580
20.

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

Ramsey JD, Spirtes P, Glymour C.

Neuroimage. 2011 Jul 15;57(2):323-30. doi: 10.1016/j.neuroimage.2010.07.065. Epub 2010 Aug 12.

PMID:
20709178
21.

Comorbid science?

Danks D, Fancsali S, Glymour C, Scheines R.

Behav Brain Sci. 2010 Jun;33(2-3):153-5. doi: 10.1017/S0140525X10000609.

PMID:
20584373
22.

Six problems for causal inference from fMRI.

Ramsey JD, Hanson SJ, Hanson C, Halchenko YO, Poldrack RA, Glymour C.

Neuroimage. 2010 Jan 15;49(2):1545-58. doi: 10.1016/j.neuroimage.2009.08.065. Epub 2009 Sep 9.

PMID:
19747552
23.

Preschool children learn about causal structure from conditional interventions.

Schulz LE, Gopnik A, Glymour C.

Dev Sci. 2007 May;10(3):322-32.

PMID:
17444973
24.

Concerns about unreliable data from spotted cDNA microarrays due to cross-hybridization and sequence errors.

Handley D, Serban N, Peters DG, Glymour C.

Stat Appl Genet Mol Biol. 2004;3:Article25. Epub 2004 Oct 6.

PMID:
16646804
25.

Optical coherence tomography machine learning classifiers for glaucoma detection: a preliminary study.

Burgansky-Eliash Z, Wollstein G, Chu T, Ramsey JD, Glymour C, Noecker RJ, Ishikawa H, Schuman JS.

Invest Ophthalmol Vis Sci. 2005 Nov;46(11):4147-52.

26.

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

Handley D, Serban N, Peters D, O'Doherty R, Field M, Wasserman L, Spirtes P, Scheines R, Glymour C.

Genomics. 2004 Jun;83(6):1169-75.

PMID:
15177570
27.

A theory of causal learning in children: causal maps and Bayes nets.

Gopnik A, Glymour C, Sobel DM, Schulz LE, Kushnir T, Danks D.

Psychol Rev. 2004 Jan;111(1):3-32. Review.

28.

A statistical problem for inference to regulatory structure from associations of gene expression measurements with microarrays.

Chu T, Glymour C, Scheines R, Spirtes P.

Bioinformatics. 2003 Jun 12;19(9):1147-52.

PMID:
12801876
29.

Learning, prediction and causal Bayes nets.

Glymour C.

Trends Cogn Sci. 2003 Jan;7(1):43-48.

PMID:
12517358
30.
31.

Reply to Comments.

Schienes R, Spirtes P, Glymour C, Meek C, Richardson T.

Multivariate Behav Res. 1998 Jan 1;33(1):165-80. doi: 10.1207/s15327906mbr3301_8.

PMID:
26771759
32.

The TETRAD Project: Constraint Based Aids to Causal Model Specification.

Scheines R, Spirtes P, Glymour C, Meek C, Richardson T.

Multivariate Behav Res. 1998 Jan 1;33(1):65-117. doi: 10.1207/s15327906mbr3301_3.

PMID:
26771754
33.

An evaluation of machine-learning methods for predicting pneumonia mortality.

Cooper GF, Aliferis CF, Ambrosino R, Aronis J, Buchanan BG, Caruana R, Fine MJ, Glymour C, Gordon G, Hanusa BH, Janosky JE, Meek C, Mitchell T, Richardson T, Spirtes P.

Artif Intell Med. 1997 Feb;9(2):107-38.

PMID:
9040894
35.

TETRAD: Discovering Causal Structure.

Glymour C, Scheines R, Spirtes P, Kelly K.

Multivariate Behav Res. 1988 Apr 1;23(2):279-80. doi: 10.1207/s15327906mbr2302_13. No abstract available.

PMID:
26764954
36.

Sounding board. Engineers, cranks, physicians, magicians.

Glymour C, Stalker D.

N Engl J Med. 1983 Apr 21;308(16):960-4. No abstract available.

PMID:
6835298

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