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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 1261–1270 of 1722 papers

Title	Date	Tasks	Status	Hype
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges	Mar 20, 2021	Additive modelsBIG-bench Machine Learning	—Unverified	0
Time-uniform central limit theory and asymptotic confidence sequences	Mar 11, 2021	Causal Inferencevalid	CodeCode Available	0
Estimating the causal effect of an intervention in a time series setting: the C-ARIMA approach	Mar 11, 2021	Causal InferenceEconometrics	—Unverified	0
Combining Interventional and Observational Data Using Causal Reductions	Mar 8, 2021	Causal Inference	CodeCode Available	0
Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity	Mar 6, 2021	Causal Inferencereinforcement-learning	—Unverified	0
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks	Mar 2, 2021	Causal InferenceMissing Values	—Unverified	0
Confronting Machine Learning With Financial Research	Feb 28, 2021	BIG-bench Machine LearningCausal Inference	—Unverified	0
Scalable Causal Domain Adaptation	Feb 27, 2021	Causal DiscoveryCausal Inference	CodeCode Available	0
Case Level Counterfactual Reasoning in Process Mining	Feb 25, 2021	Causal Inferencecounterfactual	—Unverified	0
Online Multi-Armed Bandits with Adaptive Inference	Feb 25, 2021	Causal InferenceDecision Making	—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