Home
About
Advanced Search
Browse by Discipline
Scientific Societies
E-print Alerts
Add E-prints
FAQ
•
HELP
•
SITE MAP
•
CONTACT US
Search
Advanced Search
Tian, Jin - Department of Computer Science, Iowa State University
Computing Posterior Probabilities of Structural Features in Bayesian Networks
Parameter Identification in a Class of Linear Structural Equation Models Department of Computer Science
Markov Properties for Linear Causal Models with Correlated Errors Markov Properties for Linear Causal Models with
Identifying Dynamic Sequential Plans Department of Computer Science
Bounds on Direct Effects in the Presence of Confounded Intermediate Variables
Let X be a treatment variable, Z be an outcome variable, and rz be a map-ping variable from X to Z. To represent the four potential response types, we
Polynomial Constraints in Causal Bayesian Networks Changsung Kang
Inequality Constraints in Causal Models with Hidden Variables Changsung Kang
A Hybrid Generative/Discriminative Bayesian Classifier Changsung Kang and Jin Tian
Identifying Conditional Causal Effects Department of Computer Science
On the Identification of Causal Effects Department of Computer Science
On the Identification of a Class of Linear Models Department of Computer Science
A Criterion for Parameter Identification in Structural Equation Models Department of Computer Science
Generating Markov Equivalent Maximal Ancestral Graphs by Single Edge Replacement
Identifying Linear Causal Effects Department of Computer Science
Identifying Direct Causal Effects in Linear Models Department of Computer Science
A General Identification Condition for Causal Effects Jin Tian and Judea Pearl
Local Markov Property for Models Satisfying Composition Axiom Changsung Kang
A Characterization of Interventional Distributions in Semi-Markovian Causal Jin Tian and Changsung Kang