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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 211–220 of 1722 papers

Title	Date	Tasks	Status	Hype
A Causal Inference Approach for Quantifying Research Impact	Mar 7, 2025	Causal Inferencecounterfactual	—Unverified	0
A Multi-class Ride-hailing Service Subsidy System Utilizing Deep Causal Networks	Aug 4, 2024	Causal Inference	—Unverified	0
An AI-powered Bayesian generative modeling approach for causal inference in observational studies	Jan 1, 2025	Causal InferenceUncertainty Quantification	—Unverified	0
CaM-Gen: Causally Aware Metric-Guided Text Generation	May 1, 2022	Causal InferenceText Generation	—Unverified	0
Active and Passive Causal Inference Learning	Aug 18, 2023	Causal IdentificationCausal Inference	—Unverified	0
A Mixing Time Lower Bound for a Simplified Version of BART	Oct 17, 2022	Causal Inferenceregression	—Unverified	0
A Causal Framework for Precision Rehabilitation	Nov 6, 2024	Causal Inference	—Unverified	0
Can predictive models be used for causal inference?	Jun 18, 2023	Causal Inferencefeature selection	—Unverified	0
Categoroids: Universal Conditional Independence	Aug 23, 2022	Causal Inference	—Unverified	0
Action needed to make carbon offsets from tropical forest conservation work for climate change mitigation	Jan 5, 2023	AttributeCausal 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