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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 891–900 of 1722 papers

Title	Date	Tasks	Status	Hype
Proximal Causal Learning of Conditional Average Treatment Effects	Jan 26, 2023	Causal InferenceMarketing	—Unverified	0
Causal Inference under Data Restrictions	Jan 20, 2023	Causal Inferencecounterfactual	—Unverified	0
Non-parametric identifiability and sensitivity analysis of synthetic control models	Jan 18, 2023	Causal InferenceSensitivity	—Unverified	0
Optimal Transport for Counterfactual Estimation: A Method for Causal Inference	Jan 18, 2023	Causal Inferencecounterfactual	CodeCode Available	0
Causal Falsification of Digital Twins	Jan 17, 2023	Causal Inference	CodeCode Available	0
Interacting Treatments with Endogenous Takeup	Jan 12, 2023	Causal Inference	—Unverified	0
Subset verification and search algorithms for causal DAGs	Jan 9, 2023	Causal Inference	CodeCode Available	0
Causal Inference for Recommendation: Foundations, Methods and Applications	Jan 8, 2023	Causal InferenceFairness	—Unverified	0
Action needed to make carbon offsets from tropical forest conservation work for climate change mitigation	Jan 5, 2023	AttributeCausal Inference	—Unverified	0
Continual Causal Effect Estimation: Challenges and Opportunities	Jan 3, 2023	Causal Inferencecounterfactual	—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