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Causal Inference

Causal inference is the task of drawing a conclusion about a causal connection based on the conditions of the occurrence of an effect.

( Image credit: Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data )

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1431–1440 of 1722 papers

Title	Date	Tasks	Status	Hype
Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond	Dec 30, 2019	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data	Dec 22, 2019	Causal Inferencecounterfactual	—Unverified	0
Causal Inference and Data Fusion in Econometrics	Dec 19, 2019	Causal InferenceEconometrics	—Unverified	0
Network Data	Dec 13, 2019	Causal Inferenceregression	—Unverified	0
More Efficient Off-Policy Evaluation through Regularized Targeted Learning	Dec 13, 2019	Causal InferenceOff-policy evaluation	—Unverified	0
MetaCI: Meta-Learning for Causal Inference in a Heterogeneous Population	Dec 9, 2019	Causal Inferencecounterfactual	—Unverified	0
Using Machine Learning to Assess Short Term Causal Dependence and Infer Network Links	Dec 5, 2019	BIG-bench Machine LearningCausal Inference	—Unverified	0
Variance Reduction in Bipartite Experiments through Correlation Clustering	Dec 1, 2019	Causal InferenceClustering	—Unverified	0
Deep representation learning for individualized treatment effect estimation using electronic health records	Dec 1, 2019	Causal Inferencecounterfactual	CodeCode Available	0
Perceiving the arrow of time in autoregressive motion	Dec 1, 2019	Causal InferenceTime Series Analysis	—Unverified	0

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All datasets IHDP Jobs IDHP

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Random Forest	Average Treatment Effect Error	0.96	—	Unverified
2	Balancing Linear Regression	Average Treatment Effect Error	0.93	—	Unverified
3	k-NN	Average Treatment Effect Error	0.79	—	Unverified
4	CEVAE	Average Treatment Effect Error	0.46	—	Unverified
5	Balancing Neural Network	Average Treatment Effect Error	0.42	—	Unverified
6	Causal Forest	Average Treatment Effect Error	0.4	—	Unverified
7	BCAUS DR	Average Treatment Effect Error	0.29	—	Unverified
8	TARNet	Average Treatment Effect Error	0.28	—	Unverified
9	Counterfactual Regression + WASS	Average Treatment Effect Error	0.27	—	Unverified
10	MTDL-KNN	Average Treatment Effect Error	0.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CFR WASS	Average Treatment Effect on the Treated Error	0.09	—	Unverified
2	CFR MMD	Average Treatment Effect on the Treated Error	0.08	—	Unverified
3	BART	Average Treatment Effect on the Treated Error	0.08	—	Unverified
4	GANITE	Average Treatment Effect on the Treated Error	0.06	—	Unverified
5	BCAUSS	Average Treatment Effect on the Treated Error	0.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BART	Average Treatment Effect Error	0.34	—	Unverified
2	OLS with separate regressors for each treatment	Average Treatment Effect Error	0.31	—	Unverified
3		Average Treatment Effect Error	-0.23	—	Unverified