Counterfactual inference considers a hypothetical intervention in a para...
Pricing decisions of companies require an understanding of the causal ef...
dynamite is an R package for Bayesian inference of intensive panel (time...
In the framework of structural causal models, counterfactual queries des...
Graphs are commonly used to represent and visualize causal relations. Fo...
Causal effect identification considers whether an interventional probabi...
We propose a general framework for realistic data generation and simulat...
Epidemiological evidence is based on multiple data sources including cli...
We consider the problem of estimating causal effects of interventions fr...
Causal effect identification considers whether an interventional probabi...
Identification of causal effects is one of the most fundamental tasks of...
Do-calculus is concerned with estimating the interventional distribution...
Causal models communicate our assumptions about causes and effects in
re...
Obtaining a non-parametric expression for an interventional distribution...