HyperAIHyperAI초신경
홈뉴스연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
전체 검색
소개
한국어
HyperAIHyperAI초신경
  1. 홈
  2. SOTA
  3. 인과추론
  4. Causal Inference On Ihdp

Causal Inference On Ihdp

평가 지표

Average Treatment Effect Error

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름
Average Treatment Effect Error
Paper TitleRepository
Dragonnet0.20Adapting Neural Networks for the Estimation of Treatment Effects
Random Forest0.96Estimating individual treatment effect: generalization bounds and algorithms
Counterfactual Regression + WASS0.27Estimating individual treatment effect: generalization bounds and algorithms
BCAUS DR0.29Minimizing bias in massive multi-arm observational studies with BCAUS: balancing covariates automatically using supervision-
Balancing Neural Network0.42Estimating individual treatment effect: generalization bounds and algorithms
MTDL-KNN0.23Deep representation learning for individualized treatment effect estimation using electronic health records-
CEVAE0.46Causal Effect Inference with Deep Latent-Variable Models
Causal Forest0.4Estimating individual treatment effect: generalization bounds and algorithms
k-NN0.79Estimating individual treatment effect: generalization bounds and algorithms
BCAUSS0.15Learning end-to-end patient representations through self-supervised covariate balancing for causal treatment effect estimation-
TARNet0.28Estimating individual treatment effect: generalization bounds and algorithms
Balancing Linear Regression0.93Estimating individual treatment effect: generalization bounds and algorithms
0 of 12 row(s) selected.
HyperAI

학습, 이해, 실천, 커뮤니티와 함께 인공지능의 미래를 구축하다

한국어

소개

회사 소개데이터셋 도움말

제품

뉴스튜토리얼데이터셋백과사전

링크

TVM 한국어Apache TVMOpenBayes

© HyperAI초신경

TwitterBilibili