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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 411–420 of 1722 papers

Title	Date	Tasks	Status	Hype
AFA-PredNet: The action modulation within predictive coding	Apr 11, 2018	Causal InferencePrediction	—Unverified	0
Causal Inference through a Witness Protection Program	Jun 2, 2014	Bayesian InferenceCausal Inference	—Unverified	0
Accounting for Missing Covariates in Heterogeneous Treatment Estimation	Oct 21, 2024	Causal Inference	—Unverified	0
Estimation and Inference on Nonlinear and Heterogeneous Effects	Mar 16, 2017	BIG-bench Machine LearningCausal Inference	—Unverified	0
Causal Effect Variational Autoencoder with Uniform Treatment	Nov 16, 2021	Causal InferenceDomain Adaptation	—Unverified	0
A Review of Generalizability and Transportability	Feb 23, 2021	Causal Inference	—Unverified	0
Causal Inference Under Approximate Neighborhood Interference	Nov 16, 2019	Causal Inference	—Unverified	0
Causal Inference under Data Restrictions	Jan 20, 2023	Causal Inferencecounterfactual	—Unverified	0
Causal Inference Under Interference And Network Uncertainty	Jun 29, 2019	Causal Inference	—Unverified	0
Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-based Approach	Feb 4, 2019	Causal IdentificationCausal Inference	—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