27 citations · 27 across the 2 of their papers we have counts for
2 papers
stat.ME2024
Hierarchical Bias-Driven Stratification for Interpretable Causal Effect Estimation
Lucile Ter-Minassian, Liran Szlak, Ehud Karavani +2
Interpretability and transparency are essential for incorporating causal effect models from observational data into policy decision-making. They can provide trust for the model in…
cs.HC2023★ 27 cited
Causalvis: Visualizations for Causal Inference
Grace Guo, Ehud Karavani, Alex Endert +1
Causal inference is a statistical paradigm for quantifying causal effects using observational data. It is a complex process, requiring multiple steps, iterations, and collaboration…