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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 1171–1180 of 1722 papers

Title	Date	Tasks	Status	Hype
Hierarchical Gaussian Process Models for Regression Discontinuity/Kink under Sharp and Fuzzy Designs	Oct 3, 2021	Causal Inferenceregression	—Unverified	0
Enhancing Model Robustness and Fairness with Causality: A Regularization Approach	Oct 3, 2021	Causal Inferencecounterfactual	CodeCode Available	0
Towards Principled Causal Effect Estimation by Deep Identifiable Models	Sep 30, 2021	Causal Inference	—Unverified	0
Minimizing Memorization in Meta-learning: A Causal Perspective	Sep 29, 2021	Causal InferenceMemorization	—Unverified	0
Generating High-Fidelity Privacy-Conscious Synthetic Patient Data for Causal Effect Estimation with Multiple Treatments	Sep 29, 2021	Causal Inference	—Unverified	0
Learning Causal Relationships from Conditional Moment Restrictions by Importance Weighting	Sep 29, 2021	Causal Inference	—Unverified	0
Automated hypothesis generation via Evolutionary Abduction	Sep 29, 2021	Causal InferenceIntent Recognition	—Unverified	0
Connecting Data to Mechanisms with Meta Structual Causal Model	Sep 29, 2021	Causal InferenceRepresentation Learning	—Unverified	0
-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap	Sep 29, 2021	Causal Inference	—Unverified	0
Mutual Information Minimization Based Disentangled Learning Framework For Causal Effect Estimation	Sep 29, 2021	Causal InferenceRepresentation Learning	—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