팔로우
Jin Tian
제목
인용
인용
연도
A general identification condition for causal effects
J Tian, J Pearl
Aaai/iaai, 567-573, 2002
4902002
Probabilities of causation: Bounds and identification
J Tian, J Pearl
Annals of Mathematics and Artificial Intelligence 28 (1), 287-313, 2000
2812000
Graphical models for inference with missing data
K Mohan, J Pearl, J Tian
Advances in neural information processing systems 26, 2013
2192013
Recovering from selection bias in causal and statistical inference
E Bareinboim, J Tian, J Pearl
Probabilistic and causal inference: The works of Judea Pearl, 433-450, 2022
2042022
Causal discovery from changes
J Tian, J Pearl
arXiv preprint arXiv:1301.2312, 2013
2032013
On the testable implications of causal models with hidden variables
J Tian, J Pearl
arXiv preprint arXiv:1301.0608, 2012
1762012
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
1292008
Finding minimal d-separators
J Tian, A Paz, J Pearl
Computer Science Department, University of California, 1998
1111998
A branch-and-bound algorithm for MDL learning Bayesian networks
J Tian
arXiv preprint arXiv:1301.3897, 2013
892013
Partial counterfactual identification from observational and experimental data
J Zhang, J Tian, E Bareinboim
International conference on machine learning, 26548-26558, 2022
792022
Recovering causal effects from selection bias
E Bareinboim, J Tian
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
782015
Estimating identifiable causal effects through double machine learning
Y Jung, J Tian, E Bareinboim
Proceedings of the AAAI Conference on Artificial Intelligence 35 (13), 12113 …, 2021
542021
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
542010
Identifying dynamic sequential plans
J Tian
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2008
53*2008
Learning causal effects via weighted empirical risk minimization
Y Jung, J Tian, E Bareinboim
Advances in neural information processing systems 33, 12697-12709, 2020
452020
Generalized adjustment under confounding and selection biases
J Correa, J Tian, E Bareinboim
Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018
442018
Joint Discovery of Skill Prerequisite Graphs and Student Models.
Y Chen, JP González-Brenes, J Tian
International Educational Data Mining Society, 2016
432016
Testable implications of linear structural equation models
B Chen, J Tian, J Pearl
Proceedings of the AAAI Conference on Artificial Intelligence 28 (1), 2014
412014
Data poisoning attacks and defenses to crowdsourcing systems
M Fang, M Sun, Q Li, NZ Gong, J Tian, J Liu
Proceedings of the web conference 2021, 969-980, 2021
402021
Inequality constraints in causal models with hidden variables
C Kang, J Tian
Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI), 2006
37*2006
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학술자료 1–20