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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 321–330 of 1722 papers

Title	Date	Tasks	Status	Hype
A Framework for Inferring Causality from Multi-Relational Observational Data using Conditional Independence	Aug 8, 2017	Causal Inference	—Unverified	0
A Survey of Event Causality Identification: Principles, Taxonomy, Challenges, and Assessment	Nov 15, 2024	Causal InferenceEvent Causality Identification	—Unverified	0
A Cautionary Tale on Integrating Studies with Disparate Outcome Measures for Causal Inference	May 16, 2025	Causal InferenceData Integration	—Unverified	0
Does Misclassifying Non-confounding Covariates as Confounders Affect the Causal Inference within the Potential Outcomes Framework?	Aug 22, 2023	Causal Inferencecounterfactual	—Unverified	0
A Forecaster's Review of Judea Pearl's Causality: Models, Reasoning and Inference, Second Edition, 2009	Aug 10, 2023	Causal InferenceTime Series	—Unverified	0
A step towards the applicability of algorithms based on invariant causal learning on observational data	Apr 5, 2023	Causal DiscoveryCausal Inference	—Unverified	0
Assimilative Causal Inference	May 20, 2025	Causal InferenceTime Series	—Unverified	0
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem	Dec 19, 2020	BIG-bench Machine LearningCausal Inference	—Unverified	0
Causal Inference for Recommendation: Foundations, Methods and Applications	Jan 8, 2023	Causal InferenceFairness	—Unverified	0
Causal Inference from Slowly Varying Nonstationary Processes	May 11, 2024	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