Jin Tian, Ph.D. - Publications
Affiliations: | 2002 | University of California, Los Angeles, Los Angeles, CA |
Area:
artificial intelligence and knowledge representation; probabilistic and causal reasoning; nonstandard logics; learning strategiesYear | Citation | Score | |||
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2015 | Bareinboim E, Tian J. Recovering causal effects from selection bias Proceedings of the National Conference On Artificial Intelligence. 5: 3475-3481. | 0.651 | |||
2014 | Bareinboim E, Tian J, Pearl J. Recovering from selection bias in causal and statistical inference Proceedings of the National Conference On Artificial Intelligence. 4: 2410-2416. | 0.641 | |||
2014 | Chen B, Tian J, Pearl J. Testable implications of linear structural equation models Proceedings of the National Conference On Artificial Intelligence. 4: 2424-2430. | 0.475 | |||
2013 | Mohan K, Pearl J, Tian J. Graphical models for inference with missing data Advances in Neural Information Processing Systems. | 0.47 | |||
2008 | Cai Z, Kuroki M, Pearl J, Tian J. Bounds on direct effects in the presence of confounded intermediate variables. Biometrics. 64: 695-701. PMID 18162106 DOI: 10.1111/J.1541-0420.2007.00949.X | 0.512 | |||
2006 | Tian J, Kang C, Pearl J. A characterizetion of interventional distributions in semi-markovian causal models Proceedings of the National Conference On Artificial Intelligence. 2: 1239-1244. | 0.487 | |||
2002 | Tian J, Pearl J. A new characterization of the experimental implications of causal bayesian networks Proceedings of the National Conference On Artificial Intelligence. 574-579. | 0.452 | |||
2002 | Tian J, Pearl J. A general identification condition for causal effects Proceedings of the National Conference On Artificial Intelligence. 567-573. | 0.463 | |||
2000 | Tian J, Pearl J. Probabilities of causation: Bounds and identification Annals of Mathematics and Artificial Intelligence. 28: 287-313. | 0.498 | |||
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