11 citations · 11 across the 4 of their papers we have counts for
4 papers
C-XGBoost: A tree boosting model for causal effect estimation
Niki Kiriakidou, Ioannis E. Livieris, Christos Diou
Causal effect estimation aims at estimating the Average Treatment Effect as well as the Conditional Average Treatment Effect of a treatment to an outcome from the available data. T…
Integrating Nearest Neighbors with Neural Network Models for Treatment Effect Estimation
Niki Kiriakidou, Christos Diou
Treatment effect estimation is of high-importance for both researchers and practitioners across many scientific and industrial domains. The abundance of observational data makes th…
An evaluation framework for comparing causal inference models
Niki Kiriakidou, Christos Diou
Estimation of causal effects is the core objective of many scientific disciplines. However, it remains a challenging task, especially when the effects are estimated from observatio…
An improved neural network model for treatment effect estimation
Niki Kiriakidou, Christos Diou
Nowadays, in many scientific and industrial fields there is an increasing need for estimating treatment effects and answering causal questions. The key for addressing these problem…