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Heterogeneous Treatment Effect Estimation

Heterogeneous treatment effect (HTE) estimation is the task of quantifying how treatment effects vary across different individuals or subgroups.

Papers

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Showing 1–10 of 38 papers

TitleStatusHype
CausalPFN: Amortized Causal Effect Estimation via In-Context LearningCode2
Estimating individual treatment effect: generalization bounds and algorithmsCode1
On Inductive Biases for Heterogeneous Treatment Effect EstimationCode1
Quasi-Oracle Estimation of Heterogeneous Treatment EffectsCode1
Exploring Transformer Backbones for Heterogeneous Treatment Effect EstimationCode1
Individualized Multi-Treatment Response Curves Estimation using RBF-net with Shared NeuronsCode0
Counterfactual Learning to Rank using Heterogeneous Treatment Effect EstimationCode0
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect EstimationCode0
Generalized Random ForestsCode0
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect EstimationCode0
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