Recent studies of two-view correspondence learning usually establish an
...
In many observational studies, researchers are often interested in study...
Salient object detection segments attractive objects in scenes. RGB and
...
We respond to comments on our paper, titled "Instrumental variable estim...
Applied researchers often claim that the risk difference is more
heterog...
Instrumental variable methods provide useful tools for inferring causal
...
Multi-armed bandit problems provide a framework to identify the optimal
...
Mediation analysis is an important tool to study casual associations in
...
Penalized likelihood models are widely used to simultaneously select
var...
Background: Interpreting results of instrumental variable (IV) analysis ...
Understanding causal relationships is one of the most important goals of...
Unobserved confounding presents a major threat to the validity of causal...
One of the principal scientific challenges in deep learning is explainin...
Instrumental variables are widely used to deal with unmeasured confoundi...
Causal inference has been increasingly reliant on observational studies ...
Alzheimer's disease is a progressive form of dementia that results in
pr...
We congratulate Engelke and Hitz on a thought-provoking paper on graphic...
Unobserved confounding presents a major threat to causal inference in
ob...
Generalized linear models, such as logistic regression, are widely used ...
Cox's proportional hazards model is one of the most popular statistical
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We consider how to quantify the causal effect from a random variable to ...
This paper studies the problem of how to choose good viewpoints for taki...