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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 891–900 of 1722 papers

Title	Date	Tasks	Status	Hype
Symbiotic bacterial network structure involved in carbon and nitrogen metabolism of wood-utilizing insect larvae	Jan 24, 2022	Causal Inference	—Unverified	0
Asymptotically Unbiased Synthetic Control Methods by Density Matching	Jul 20, 2023	Causal Inferencecounterfactual	—Unverified	0
Synthetic Potential Outcomes and Causal Mixture Identifiability	May 29, 2024	Causal Inferencecounterfactual	—Unverified	0
Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset	Oct 31, 2017	Causal Inference	—Unverified	0
T2TD: Text-3D Generation Model based on Prior Knowledge Guidance	May 25, 2023	3D Generation3D Reconstruction	—Unverified	0
Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift	Jan 30, 2025	Causal InferenceData Integration	—Unverified	0
Targeted VAE: Structured Inference and Targeted Learning for Causal Parameter Estimation	Sep 28, 2020	Causal Inferencecounterfactual	—Unverified	0
Targeting Learning: Robust Statistics for Reproducible Research	Jun 12, 2020	Causal InferenceSurvival Analysis	—Unverified	0
Task-specific experimental design for treatment effect estimation	Jun 8, 2023	Causal InferenceExperimental Design	—Unverified	0
TC-LLaVA: Rethinking the Transfer from Image to Video Understanding with Temporal Considerations	Sep 5, 2024	Causal InferencePosition	—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