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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 1501–1510 of 1722 papers

Title	Date	Tasks	Status	Hype
Privacy-Preserving Causal Inference via Inverse Probability Weighting	May 29, 2019	Causal InferenceEconometrics	—Unverified	0
Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approach	May 29, 2019	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
Sample Complexity of Sample Average Approximation for Conditional Stochastic Optimization	May 28, 2019	Causal InferenceReinforcement Learning	—Unverified	0
Dirac Delta Regression: Conditional Density Estimation with Clinical Trials	May 24, 2019	Causal InferenceDensity Estimation	CodeCode Available	0
Contrastive Fairness in Machine Learning	May 17, 2019	BIG-bench Machine LearningCausal Inference	—Unverified	0
Stability of Linear Structural Equation Models of Causal Inference	May 16, 2019	Causal InferenceSociology	—Unverified	0
An End-to-End Framework to Identify Pathogenic Social Media Accounts on Twitter	May 4, 2019	Causal Inference	—Unverified	0
Learning Information Propagation in the Dynamical Systems via Information Bottleneck Hierarchy	May 1, 2019	Causal InferenceClustering	—Unverified	0
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data	Apr 30, 2019	Causal InferenceRepresentation Learning	CodeCode Available	0
Beauty Learning and Counterfactual Inference	Apr 24, 2019	Causal DiscoveryCausal Inference	—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