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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 761–770 of 1722 papers

Title	Date	Tasks	Status	Hype
SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation Modeling	Aug 8, 2023	Causal Inference	CodeCode Available	0
Diffusion Model in Causal Inference with Unmeasured Confounders	Aug 7, 2023	Causal Inferencecounterfactual	CodeCode Available	0
Causal Effect Estimation on Hierarchical Spatial Graph Data	Aug 6, 2023	Causal InferenceTime Series	CodeCode Available	0
Scalable Computation of Causal Bounds	Aug 4, 2023	Causal Inference	—Unverified	0
Improving the Variance of Differentially Private Randomized Experiments through Clustering	Aug 2, 2023	Causal InferenceClustering	—Unverified	0
VLUCI: Variational Learning of Unobserved Confounders for Counterfactual Inference	Aug 2, 2023	Causal Inferencecounterfactual	—Unverified	0
A continuous Structural Intervention Distance to compare Causal Graphs	Jul 31, 2023	Causal Inference	—Unverified	0
Causal Inference for Banking Finance and Insurance A Survey	Jul 31, 2023	Causal InferenceSurvey	—Unverified	0
Learning sources of variability from high-dimensional observational studies	Jul 26, 2023	Causal Inference	CodeCode Available	0
De-confounding Representation Learning for Counterfactual Inference on Continuous Treatment via Generative Adversarial Network	Jul 24, 2023	Causal Inferencecounterfactual	—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