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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 11–20 of 1722 papers

Title	Date	Tasks	Status	Hype
Linear-Time Primitives for Algorithm Development in Graphical Causal Inference	Jun 18, 2025	Causal Inference	—Unverified	0
Double Machine Learning for Conditional Moment Restrictions: IV Regression, Proximal Causal Learning and Beyond	Jun 17, 2025	Causal InferenceEconometrics	—Unverified	0
Honesty in Causal Forests: When It Helps and When It Hurts	Jun 16, 2025	Causal Inference	—Unverified	0
Estimation of Treatment Effects in Extreme and Unobserved Data	Jun 16, 2025	Causal Inference	—Unverified	0
Rethinking Distributional IVs: KAN-Powered D-IV-LATE & Model Choice	Jun 15, 2025	Causal InferenceKolmogorov-Arnold Networks	—Unverified	0
Leveraging MIMIC Datasets for Better Digital Health: A Review on Open Problems, Progress Highlights, and Future Promises	Jun 15, 2025	Causal InferenceData Integration	—Unverified	0
Directed Acyclic Graph Convolutional Networks	Jun 13, 2025	Causal InferenceComputational Efficiency	—Unverified	0
Foundation Models for Causal Inference via Prior-Data Fitted Networks	Jun 12, 2025	Bayesian InferenceCausal Inference	—Unverified	0
From Images to Insights: Explainable Biodiversity Monitoring with Plain Language Habitat Explanations	Jun 12, 2025	Causal Inference	CodeCode Available	0
Towards Robust Multimodal Emotion Recognition under Missing Modalities and Distribution Shifts	Jun 12, 2025	Causal Inferencecounterfactual	CodeCode Available	1

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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