Thomas S. Richardson
TitleCited byYear
Causation, prediction, and search
P Spirtes, CN Glymour, R Scheines, D Heckerman, C Meek, G Cooper, ...
MIT press, 2000
Ancestral graph Markov models
T Richardson, P Spirtes
The Annals of Statistics 30 (4), 962-1030, 2002
Chain graph models and their causal interpretations
SL Lauritzen, TS Richardson
Journal of the Royal Statistical Society: Series B (Statistical Methodologyá…, 2002
The TETRAD project: Constraint based aids to causal model specification
R Scheines, P Spirtes, C Glymour, C Meek, T Richardson
Multivariate Behavioral Research 33 (1), 65-117, 1998
An evaluation of machine-learning methods for predicting pneumonia mortality
GF Cooper, CF Aliferis, R Ambrosino, J Aronis, BG Buchanan, R Caruana, ...
Artificial intelligence in medicine 9 (2), 107-138, 1997
Demystifying optimal dynamic treatment regimes
EEM Moodie, TS Richardson, DA Stephens
Biometrics 63 (2), 447-455, 2007
Learning high-dimensional directed acyclic graphs with latent and selection variables
D Colombo, MH Maathuis, M Kalisch, TS Richardson
The Annals of Statistics, 294-321, 2012
Markov properties for acyclic directed mixed graphs
T Richardson
Scandinavian Journal of Statistics 30 (1), 145-157, 2003
Using path diagrams as a structural equation modeling tool
P Spirtes, T Richardson, C Meek, R Scheines, C Glymour
Sociological Methods & Research 27 (2), 182-225, 1998
Causal inference in the presence of latent variables and selection bias
P Spirtes, C Meek, T Richardson
Proceedings of the Eleventh conference on Uncertainty in artificialá…, 1995
A discovery algorithm for directed cyclic graphs
T Richardson
Proceedings of the Twelfth international conference on Uncertainty iná…, 1996
Alternative graphical causal models and the identification of direct effects
JM Robins, TS Richardson
Causality and psychopathology: Finding the determinants of disorders andá…, 2010
TETRAD 3: Tools for Causal Modeling–User’s Manual
R Scheines, P Spirtes, C Glymour, C Meek, T Richardson
CMU Philosophy, 1996
Single world intervention graphs (SWIGs): A unification of the counterfactual and graphical approaches to causality
TS Richardson, JM Robins
Center for the Statistics and the Social Sciences, University of Washingtoná…, 2013
Estimation of a covariance matrix with zeros
S Chaudhuri, M Drton, TS Richardson
Biometrika 94 (1), 199-216, 2007
Boosting methodology for regression problems.
G Ridgeway, D Madigan, T Richardson
Interpretable Boosted Na´ve Bayes Classification.
G Ridgeway, D Madigan, T Richardson, J O'Kane
KDD, 101-104, 1998
An algorithm for causal inference in the presence of latent variables and selection bias
P Spirtes, C Meek, T Richardson
MIT Press, 1999
Rest-inserted loading rapidly amplifies the response of bone to small increases in strain and load cycles
S Srinivasan, BJ Ausk, SL Poliachik, SE Warner, TS Richardson, ...
Journal of applied physiology 102 (5), 1945-1952, 2007
Covariate selection for the nonparametric estimation of an average treatment effect
X De Luna, I Waernbaum, TS Richardson
Biometrika 98 (4), 861-875, 2011
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