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算力平台

Causal Inference On Ihdp

评估指标

Average Treatment Effect Error

评测结果

各个模型在此基准测试上的表现结果

Paper Title
Random Forest0.96Estimating individual treatment effect: generalization bounds and algorithms
Balancing Linear Regression0.93Estimating individual treatment effect: generalization bounds and algorithms
k-NN0.79Estimating individual treatment effect: generalization bounds and algorithms
CEVAE0.46Causal Effect Inference with Deep Latent-Variable Models
Balancing Neural Network0.42Estimating individual treatment effect: generalization bounds and algorithms
Causal Forest0.4Estimating individual treatment effect: generalization bounds and algorithms
BCAUS DR0.29Minimizing bias in massive multi-arm observational studies with BCAUS: balancing covariates automatically using supervision
TARNet0.28Estimating individual treatment effect: generalization bounds and algorithms
Counterfactual Regression + WASS0.27Estimating individual treatment effect: generalization bounds and algorithms
MTDL-KNN0.23Deep representation learning for individualized treatment effect estimation using electronic health records
Dragonnet0.20Adapting Neural Networks for the Estimation of Treatment Effects
BCAUSS0.15Learning end-to-end patient representations through self-supervised covariate balancing for causal treatment effect estimation
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Causal Inference On Ihdp | SOTA | HyperAI超神经