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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 81–90 of 1722 papers

Title	Date	Tasks	Status	Hype
A Hamiltonian Higher-Order Elasticity Framework for Dynamic Diagnostics(2HOED)	Apr 29, 2025	AnatomyCausal Inference	—Unverified	0
Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions	Apr 29, 2025	Causal InferenceFederated Learning	—Unverified	0
Inference with few treated units	Apr 28, 2025	Causal Inference	—Unverified	0
ReLU integral probability metric and its applications	Apr 26, 2025	Causal InferenceRepresentation Learning	—Unverified	0
Consistent Causal Inference of Group Effects in Non-Targeted Trials with Finitely Many Effect Levels	Apr 22, 2025	Causal Inference	—Unverified	0
Causal DAG Summarization (Full Version)	Apr 21, 2025	Causal Inference	—Unverified	0
Causality for Natural Language Processing	Apr 20, 2025	Causal InferenceDecision Making	—Unverified	0
Dynamic Regularized CBDT: Variance-Calibrated Causal Boosting for Interpretable Heterogeneous Treatment Effects	Apr 18, 2025	Causal InferenceHeterogeneous Treatment Effect Estimation	—Unverified	0
The heterogeneous causal effects of the EU's Cohesion Fund	Apr 17, 2025	Causal Inference	—Unverified	0
Eco-efficiency as a Catalyst for Citizen Co-production: Evidence from Chinese Cities	Apr 17, 2025	Causal 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