Data Generating Process Simulation: The opossum package
Generating datasets with observed treatment effects for model evaluation
Efficient Experiments Through Inverse Propensity Score Weighting
Making A/B tests / randomised controlled trials more efficient through inverse propensity score weighting.
Matching Methods for Causal Inference: A Machine Learning Update
Matching Methods for causal inference
Uplift Modelling with Multiple Treatments
Evaluation and discussion of Uplift Models for multiple possible treatments in the area of Marketing Analytics.
Social Pressure and Voter Turnout - A Causal Machine Learning Approach
Using Causal Machine Learning to optimise the impact of voter targeting campaigns.
Marketing Campaign Optimization: Profit modeling
Using real world online shop data to model and predict treatment effects on continuous variables, aiming for profit optimization
Correcting for Self-selection in Product Rating: Causal Recommender Systems
How Can We Account for Causal Effects in Recommendation Framework