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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 451–460 of 1722 papers

Title	Date	Tasks	Status	Hype
Towards Representation Learning for Weighting Problems in Design-Based Causal Inference	Sep 24, 2024	Causal InferenceRepresentation Learning	CodeCode Available	0
From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding	Sep 23, 2024	Causal InferenceMeta-Learning	—Unverified	0
CauSkelNet: Causal Representation Learning for Human Behaviour Analysis	Sep 23, 2024	Causal InferenceRepresentation Learning	—Unverified	0
Causal Inference with Double/Debiased Machine Learning for Evaluating the Health Effects of Multiple Mismeasured Pollutants	Sep 22, 2024	Causal Inferenceregression	—Unverified	0
Testing Causal Models with Hidden Variables in Polynomial Delay via Conditional Independencies	Sep 22, 2024	Causal Inference	CodeCode Available	0
Mining Causality: AI-Assisted Search for Instrumental Variables	Sep 21, 2024	Causal Inferencecounterfactual	—Unverified	0
A Way to Synthetic Triple Difference	Sep 18, 2024	Causal Inference	—Unverified	0
Performance of Cross-Validated Targeted Maximum Likelihood Estimation	Sep 17, 2024	Causal Inferenceregression	CodeCode Available	0
Causal Inference with Large Language Model: A Survey	Sep 15, 2024	Causal InferenceLanguage Modeling	—Unverified	0
Unconditional Randomization Tests for Interference	Sep 14, 2024	Causal Inferencevalid	—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