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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 1241–1250 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Development	Dec 23, 2023	Causal InferenceEpidemiology	—Unverified	0	0
An Introduction to Causal Discovery	Jul 11, 2024	Causal DiscoveryCausal Inference	—Unverified	0	0
Causal Inference in medicine and in health policy, a summary	May 10, 2021	BIG-bench Machine LearningCausal Inference	—Unverified	0	0
An introduction to flexible methods for policy evaluation	Oct 1, 2019	Causal Inference	—Unverified	0	0
A novel approach to the relationships between data features -- based on comprehensive examination of mathematical, technological, and causal methodology	Feb 20, 2025	Causal Inferencecounterfactual	—Unverified	0	0
A Novel Method to Metigate Demographic and Expert Bias in ICD Coding with Causal Inference	Oct 18, 2024	Causal Inferencecounterfactual	—Unverified	0	0
A Novel Two-level Causal Inference Framework for On-road Vehicle Quality Issues Diagnosis	Mar 31, 2023	Causal Inference	—Unverified	0	0
An Overview of Causal Inference using Kernel Embeddings	Oct 30, 2024	Causal Inference	—Unverified	0	0
An Overview of Large Language Models for Statisticians	Feb 25, 2025	Causal InferenceDecision Making	—Unverified	0	0
An R package for parametric estimation of causal effects	Jul 17, 2023	Causal Inference	—Unverified	0	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