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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 871–880 of 1722 papers

Title	Date	Tasks	Status	Hype
Unifying Causal Inference and Reinforcement Learning using Higher-Order Category Theory	Sep 13, 2022	Causal Inferencereinforcement-learning	—Unverified	0
Normalizing Flows for Interventional Density Estimation	Sep 13, 2022	Causal InferenceDensity Estimation	CodeCode Available	0
Variational Causal Inference	Sep 13, 2022	Causal Inferencecounterfactual	CodeCode Available	1
Smiles in Profiles: Improving Efficiency While Reducing Disparities in Online Marketplaces	Sep 2, 2022	Causal Inferencecounterfactual	—Unverified	0
The Impact of the #MeToo Movement on Language at Court -- A text-based causal inference approach	Sep 1, 2022	Causal InferenceSentiment Analysis	—Unverified	0
An evaluation framework for comparing causal inference models	Aug 31, 2022	BenchmarkingCausal Inference	—Unverified	0
Data-Driven Influence Functions for Optimization-Based Causal Inference	Aug 29, 2022	Causal Inference	—Unverified	0
Virtual Control Group: Measuring Hidden Performance Metrics	Aug 27, 2022	BlockingCausal Inference	—Unverified	0
Causal Inference in Recommender Systems: A Survey and Future Directions	Aug 26, 2022	Causal InferenceClick-Through Rate Prediction	CodeCode Available	1
Categoroids: Universal Conditional Independence	Aug 23, 2022	Causal 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