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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 1451–1460 of 1722 papers

Title	Date	Tasks	Status	Hype
ρ-GNF: A Copula-based Sensitivity Analysis to Unobserved Confounding Using Normalizing Flows	Sep 15, 2022	Causal InferenceSensitivity	CodeCode Available	0
Double Robust Representation Learning for Counterfactual Prediction	Oct 15, 2020	Causal Inferencecounterfactual	CodeCode Available	0
Double Robust Semi-Supervised Inference for the Mean: Selection Bias under MAR Labeling with Decaying Overlap	Apr 14, 2021	Causal InferenceSelection bias	CodeCode Available	0
Double Trouble: How to not explain a text classifier's decisions using counterfactuals synthesized by masked language models?	Oct 22, 2021	Causal Inference	CodeCode Available	0
Targeted Estimation of Heterogeneous Treatment Effect in Observational Survival Analysis	Oct 20, 2019	Causal InferenceSurvival Analysis	CodeCode Available	0
Time-uniform central limit theory and asymptotic confidence sequences	Mar 11, 2021	Causal Inferencevalid	CodeCode Available	0
Doubly robust identification of treatment effects from multiple environments	Mar 18, 2025	Causal Inference	CodeCode Available	0
Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments	Jan 12, 2025	Causal Inference	CodeCode Available	0
Doubly Robust Kernel Statistics for Testing Distributional Treatment Effects	Dec 9, 2022	Causal Inferencecounterfactual	CodeCode Available	0
Moment-Matching Graph-Networks for Causal Inference	Jul 20, 2020	Causal InferenceGraph Neural Network	CodeCode Available	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