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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 1051–1060 of 1722 papers

Title	Date	Tasks	Status	Hype
A unified theory of information transfer and causal relation	Apr 21, 2022	Causal InferenceRelation	—Unverified	0
Interventional Multi-Instance Learning with Deconfounded Instance-Level Prediction	Apr 20, 2022	Causal InferencePrediction	—Unverified	0
Causal Intervention for Subject-Deconfounded Facial Action Unit Recognition	Apr 17, 2022	Causal InferenceFacial Action Unit Detection	—Unverified	0
Causal Disentanglement with Network Information for Debiased Recommendations	Apr 14, 2022	Causal InferenceDisentanglement	—Unverified	0
Machine Learning and Deep Learning -- A review for Ecologists	Apr 11, 2022	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
Causal Discovery and Causal Learning for Fire Resistance Evaluation: Incorporating Domain Knowledge	Apr 11, 2022	Causal DiscoveryCausal Inference	—Unverified	0
Causality, Causal Discovery, and Causal Inference in Structural Engineering	Apr 4, 2022	Causal DiscoveryCausal Inference	—Unverified	0
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data	Mar 29, 2022	Causal DiscoveryCausal Inference	CodeCode Available	0
SurvCaus : Representation Balancing for Survival Causal Inference	Mar 29, 2022	Causal Inferencecounterfactual	CodeCode Available	0
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets	Mar 29, 2022	Causal InferenceDomain Adaptation	CodeCode Available	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