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Evaluating Causal Models by Comparing Interventional Distributions

Evaluating Causal Models by Comparing Interventional Distributions

16 August 2016
Dan Garant
David D. Jensen
    CML
ArXivPDFHTML

Papers citing "Evaluating Causal Models by Comparing Interventional Distributions"

8 / 8 papers shown
Title
Learning Bayesian Networks: The Combination of Knowledge and Statistical
  Data
Learning Bayesian Networks: The Combination of Knowledge and Statistical Data
David Heckerman
D. Geiger
D. M. Chickering
TPM
115
3,982
0
27 Feb 2013
Testing Identifiability of Causal Effects
Testing Identifiability of Causal Effects
D. Galles
Judea Pearl
CML
60
90
0
20 Feb 2013
Finding Optimal Bayesian Networks
Finding Optimal Bayesian Networks
D. M. Chickering
Christopher Meek
TPM
89
152
0
12 Dec 2012
Adjacency-Faithfulness and Conservative Causal Inference
Adjacency-Faithfulness and Conservative Causal Inference
Joseph Ramsey
Jiji Zhang
Peter Spirtes
105
276
0
27 Jun 2012
Bayesian structure learning using dynamic programming and MCMC
Bayesian structure learning using dynamic programming and MCMC
Daniel Eaton
Kevin P. Murphy
77
136
0
20 Jun 2012
On the Validity of Covariate Adjustment for Estimating Causal Effects
On the Validity of Covariate Adjustment for Estimating Causal Effects
I. Shpitser
T. VanderWeele
J. M. Robins
CML
95
205
0
15 Mar 2012
Searching for Bayesian Network Structures in the Space of Restricted
  Acyclic Partially Directed Graphs
Searching for Bayesian Network Structures in the Space of Restricted Acyclic Partially Directed Graphs
Silvia Acid
L. M. D. Campos
157
135
0
30 Jun 2011
Learning high-dimensional directed acyclic graphs with latent and
  selection variables
Learning high-dimensional directed acyclic graphs with latent and selection variables
Diego Colombo
Marloes H. Maathuis
M. Kalisch
Thomas S. Richardson
CML
123
466
0
29 Apr 2011
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