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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 1411–1420 of 1722 papers

Title	Date	Tasks	Status	Hype
Causal Inference of Script Knowledge	Apr 2, 2020	Causal Inference	—Unverified	0
Quantifying the Economic Impact of Extreme Shocks on Businesses using Human Mobility Data: a Bayesian Causal Inference Approach	Apr 1, 2020	Causal Inferencecounterfactual	—Unverified	0
ParKCa: Causal Inference with Partially Known Causes	Mar 17, 2020	Causal Inferencecounterfactual	CodeCode Available	0
Interpretable Personalization via Policy Learning with Linear Decision Boundaries	Mar 17, 2020	Bayesian OptimizationBIG-bench Machine Learning	—Unverified	0
Targeting customers under response-dependent costs	Mar 13, 2020	Causal InferenceMarketing	CodeCode Available	0
Towards Clarifying the Theory of the Deconfounder	Mar 10, 2020	Causal Inference	—Unverified	0
Deconfounded Image Captioning: A Causal Retrospect	Mar 9, 2020	Causal InferenceImage Captioning	—Unverified	0
Who Make Drivers Stop? Towards Driver-centric Risk Assessment: Risk Object Identification via Causal Inference	Mar 5, 2020	Causal InferenceObject	—Unverified	0
Causal Inference With Selectively Deconfounded Data	Feb 25, 2020	Causal Inference	—Unverified	0
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning	Feb 25, 2020	Causal InferenceMeta-Learning	—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