Jin Tian
Title
Cited by
Cited by
Year
A general identification condition for causal effects
J Tian, J Pearl
Aaai/iaai, 567-573, 2002
3312002
Probabilities of causation: Bounds and identification
J Tian, J Pearl
Annals of Mathematics and Artificial Intelligence 28 (1), 287-313, 2000
1622000
Causal discovery from changes
J Tian, J Pearl
arXiv preprint arXiv:1301.2312, 2013
1462013
Graphical models for inference with missing data
K Mohan
UCLA, 2017
145*2017
On the testable implications of causal models with hidden variables
J Tian, J Pearl
arXiv preprint arXiv:1301.0608, 2012
1392012
Bounds on direct effects in the presence of confounded intermediate variables
Z Cai, M Kuroki, J Pearl, J Tian
Biometrics 64 (3), 695-701, 2008
1192008
Recovering from selection bias in causal and statistical inference
E Bareinboim, J Tian, J Pearl
Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
1072014
Finding minimal d-separators
J Tian, A Paz, J Pearl
Computer Science Department, University of California, 1998
911998
A branch-and-bound algorithm for MDL learning Bayesian networks
J Tian
arXiv preprint arXiv:1301.3897, 2013
782013
On the identification of causal effects
J Tian, J Pearl
UCLA Cognitive Systems Laboratory, Technical Report (R-290-L), 2002
592002
Bayesian model averaging using the k-best Bayesian network structures
J Tian, R He, L Ram
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2010
452010
Recovering causal effects from selection bias
E Bareinboim, J Tian
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
442015
Identifying dynamic sequential plans
J Tian
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2008
41*2008
Inequality constraints in causal models with hidden variables
C Kang, J Tian
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2006
34*2006
Identifying direct causal effects in linear models
J Tian
AAAI, 346-353, 2005
322005
Computing posterior probabilities of structural features in Bayesian networks
J Tian, R He
arXiv preprint arXiv:1205.2612, 2012
312012
Identifying conditional causal effects
J Tian
arXiv preprint arXiv:1207.4161, 2012
292012
Testable implications of linear structural equation models
B Chen, J Tian, J Pearl
Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014
282014
Joint Discovery of Skill Prerequisite Graphs and Student Models.
Y Chen, JP González-Brenes, J Tian
International Educational Data Mining Society, 2016
262016
Markov Properties for Linear Causal Models with Correlated Errors.
C Kang, J Tian
Journal of Machine Learning Research 10 (1), 2009
252009
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Articles 1–20