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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 1331–1340 of 1722 papers

Title	Date	Tasks	Status	Hype
Semi-supervised learning and the question of true versus estimated propensity scores	Sep 14, 2020	Causal Inference	CodeCode Available	0
Local Composite Quantile Regression for Regression Discontinuity	Sep 8, 2020	Causal Inferencequantile regression	—Unverified	0
Quantifying the Causal Effects of Conversational Tendencies	Sep 8, 2020	Causal Inference	—Unverified	0
Causal Inference in Possibly Nonlinear Factor Models	Aug 31, 2020	Causal Inferencecounterfactual	CodeCode Available	0
Path Dependent Structural Equation Models	Aug 24, 2020	Causal Inference	—Unverified	0
Hi-CI: Deep Causal Inference in High Dimensions	Aug 22, 2020	Causal Inferencecounterfactual	—Unverified	0
Long-Term Effect Estimation with Surrogate Representation	Aug 19, 2020	Causal Inference	CodeCode Available	1
Estimation of causal effects of multiple treatments in healthcare database studies with rare outcomes	Aug 18, 2020	Causal Inferenceregression	—Unverified	0
Estimating heterogeneous survival treatment effect in observational data using machine learning	Aug 17, 2020	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
Estimating Causal Effects with the Neural Autoregressive Density Estimator	Aug 17, 2020	Causal Inference	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