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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 901–910 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Potential Field as Scene Affordance for Behavior Change-Based Visual Risk Object Identification	Sep 24, 2024	Causal InferenceComputational Efficiency	—Unverified	0	0
Potential weights and implicit causal designs in linear regression	Jul 30, 2024	Causal Inferencecounterfactual	—Unverified	0	0
Practically Effective Adjustment Variable Selection in Causal Inference	Feb 4, 2025	Causal InferenceVariable Selection	—Unverified	0	0
Practical programming research of Linear DML model based on the simplest Python code: From the standpoint of novice researchers	Feb 22, 2025	Causal Inference	—Unverified	0	0
Predictive Incrementality by Experimentation (PIE) for Ad Measurement	Apr 13, 2023	Causal InferenceDecision Making	—Unverified	0	0
PresAIse, A Prescriptive AI Solution for Enterprises	Feb 3, 2024	Causal InferenceDecision Making	—Unverified	0	0
Prescriptive maintenance with causal machine learning	Jun 3, 2022	BIG-bench Machine LearningCausal Inference	—Unverified	0	0
Principal Fairness for Human and Algorithmic Decision-Making	May 21, 2020	Causal Inferencecounterfactual	—Unverified	0	0
Private Causal Inference	Dec 17, 2015	Causal Inference	—Unverified	0	0
Privacy-Preserving Causal Inference via Inverse Probability Weighting	May 29, 2019	Causal InferenceEconometrics	—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