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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 1171–1180 of 1722 papers

Title	Date	Tasks	Status	Hype
From Correlation to Causation: Understanding Climate Change through Causal Analysis and LLM Interpretations	Dec 21, 2024	Causal InferenceDecision Making	—Unverified	0
From Dependence to Causation	Jul 12, 2016	BIG-bench Machine LearningCausal Inference	—Unverified	0
From dependency to causality: a machine learning approach	Dec 19, 2014	BIG-bench Machine LearningCausal Inference	—Unverified	0
From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation	Mar 26, 2022	Causal InferenceInformation Retrieval	—Unverified	0
From Prompts to Constructs: A Dual-Validity Framework for LLM Research in Psychology	Jun 20, 2025	Causal Inference	—Unverified	0
From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding	Sep 23, 2024	Causal InferenceMeta-Learning	—Unverified	0
From What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI	May 19, 2025	Causal Inferencecounterfactual	—Unverified	0
GCF: Generalized Causal Forest for Heterogeneous Treatment Effect Estimation in Online Marketplace	Mar 21, 2022	Causal InferenceDecision Making	—Unverified	0
Generalization bound for estimating causal effects from observational network data	Aug 8, 2023	Causal InferenceRepresentation Learning	—Unverified	0
Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection	Nov 9, 2021	Causal Inferencecounterfactual	—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