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Causal Inference On Ihdp

Métriques

Average Treatment Effect Error

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Average Treatment Effect Error	Paper Title	Repository
Dragonnet	0.20	Adapting Neural Networks for the Estimation of Treatment Effects
Random Forest	0.96	Estimating individual treatment effect: generalization bounds and algorithms
Counterfactual Regression + WASS	0.27	Estimating individual treatment effect: generalization bounds and algorithms
BCAUS DR	0.29	Minimizing bias in massive multi-arm observational studies with BCAUS: balancing covariates automatically using supervision	-
Balancing Neural Network	0.42	Estimating individual treatment effect: generalization bounds and algorithms
MTDL-KNN	0.23	Deep representation learning for individualized treatment effect estimation using electronic health records
CEVAE	0.46	Causal Effect Inference with Deep Latent-Variable Models
Causal Forest	0.4	Estimating individual treatment effect: generalization bounds and algorithms
k-NN	0.79	Estimating individual treatment effect: generalization bounds and algorithms
BCAUSS	0.15	Learning end-to-end patient representations through self-supervised covariate balancing for causal treatment effect estimation
TARNet	0.28	Estimating individual treatment effect: generalization bounds and algorithms
Balancing Linear Regression	0.93	Estimating individual treatment effect: generalization bounds and algorithms

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