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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 1511–1520 of 1722 papers

Title	Date	Tasks	Status	Hype
A unifying approach for doubly-robust _1 regularized estimation of causal contrasts	Apr 7, 2019	Causal InferenceEconometrics	—Unverified	0
What can be estimated? Identifiability, estimability, causal inference and ill-posed inverse problems	Apr 4, 2019	Causal Inference	—Unverified	0
Machine Learning Methods Economists Should Know About	Mar 24, 2019	BIG-bench Machine LearningCausal Inference	—Unverified	0
Size of Interventional Markov Equivalence Classes in Random DAG Models	Mar 5, 2019	Causal InferenceExperimental Design	—Unverified	0
Machine learning in policy evaluation: new tools for causal inference	Mar 1, 2019	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
On Robustness of Principal Component Regression	Feb 28, 2019	Art AnalysisCausal Inference	—Unverified	0
On Multi-Cause Causal Inference with Unobserved Confounding: Counterexamples, Impossibility, and Alternatives	Feb 27, 2019	Causal InferenceSensitivity	—Unverified	0
Classifying Treatment Responders Under Causal Effect Monotonicity	Feb 14, 2019	Causal InferenceClassification	—Unverified	0
Robust Multi-instance Learning with Stable Instances	Feb 13, 2019	Causal Inferenceimage-classification	—Unverified	0
Weighted Tensor Completion for Time-Series Causal Inference	Feb 12, 2019	Causal InferenceTime Series	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