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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 1391–1400 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Causal Graph Aided Causal Discovery in an Observational Aneurysmal Subarachnoid Hemorrhage Study	Aug 12, 2024	Causal DiscoveryCausal Inference	—Unverified	0	0
Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models	Feb 23, 2024	Causal InferenceRetrieval	—Unverified	0	0
Causal Identification with Additive Noise Models: Quantifying the Effect of Noise	Oct 15, 2021	Causal DiscoveryCausal Identification	—Unverified	0	0
Identifying causal effects with subjective ordinal outcomes	Dec 30, 2022	Causal IdentificationCausal Inference	—Unverified	0	0
Causal Inference and Data Fusion in Econometrics	Dec 19, 2019	Causal InferenceEconometrics	—Unverified	0	0
Causal inference approach to appraise long-term effects of maintenance policy on functional performance of asphalt pavements	May 6, 2024	Causal Inference	—Unverified	0	0
Causal Inference Based Single-branch Ensemble Trees For Uplift Modeling	Feb 3, 2023	Causal Inference	—Unverified	0	0
Causal Inference based Transfer Learning with LLMs: An Efficient Framework for Industrial RUL Prediction	Mar 22, 2025	Causal InferenceComputational Efficiency	—Unverified	0	0
Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components	Nov 14, 2014	Causal InferenceTime Series	—Unverified	0	0
Causal Inference by Stochastic Complexity	Feb 22, 2017	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