SOTAVerified

Heterogeneous Treatment Effect Estimation

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

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 11–20 of 38 papers

TitleStatusHype
Stable Heterogeneous Treatment Effect Estimation across Out-of-Distribution PopulationsCode0
TabPFN: One Model to Rule Them All?Code0
Uncertainty Quantification in Heterogeneous Treatment Effect Estimation with Gaussian-Process-Based Partially Linear ModelCode0
Differentiable Pareto-Smoothed Weighting for High-Dimensional Heterogeneous Treatment Effect EstimationCode0
Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event DataCode0
Counterfactual Learning to Rank using Heterogeneous Treatment Effect EstimationCode0
Improving Data-driven Heterogeneous Treatment Effect Estimation Under Structure UncertaintyCode0
Individualized Multi-Treatment Response Curves Estimation using RBF-net with Shared NeuronsCode0
In Search of Insights, Not Magic Bullets: Towards Demystification of the Model Selection Dilemma in Heterogeneous Treatment Effect EstimationCode0
Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark—0
Show:102550
← PrevPage 2 of 4Next →

No leaderboard results yet.