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06/11/2022
Greedy Relaxations of the Sparsest Permutation Algorithm
There has been an increasing interest in methods that exploit permutatio...
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02/25/2022
Causal discovery for observational sciences using supervised machine learning
Causal inference can estimate causal effects, but unless data are collec...
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03/26/2021
FRITL: A Hybrid Method for Causal Discovery in the Presence of Latent Confounders
We consider the problem of estimating a particular type of linear non-Ga...
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03/05/2019
Causal Discovery and Hidden Driving Force Estimation from Nonstationary/Heterogeneous Data
It is commonplace to encounter nonstationary or heterogeneous data. Such...
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01/27/2019
Diagnosis of Autism Spectrum Disorder by Causal Influence Strength Learned from Resting-State fMRI Data
Autism spectrum disorder (ASD) is one of the major developmental disorde...
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05/06/2018
FASK with Interventional Knowledge Recovers Edges from the Sachs Model
We report a procedure that, in one step from continuous data with minima...
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06/10/2017
Causal Discovery in the Presence of Measurement Error: Identifiability Conditions
Measurement error in the observed values of the variables can greatly ch...
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10/03/2016
Improving Accuracy and Scalability of the PC Algorithm by Maximizing P-value
A number of attempts have been made to improve accuracy and/or scalabili...
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06/13/2012
Discovering Cyclic Causal Models by Independent Components Analysis
We generalize Shimizu et al's (2006) ICA-based approach for discovering ...
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06/13/2012