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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 1661–1670 of 1722 papers

Title	Date	Tasks	Status	Hype
Ancestral Causal Inference	Jun 22, 2016	Causal DiscoveryCausal Inference	CodeCode Available	0
The Crossover Process: Learnability and Data Protection from Inference Attacks	Jun 13, 2016	Causal InferenceFairness	—Unverified	0
Causal Bandits: Learning Good Interventions via Causal Inference	Jun 10, 2016	Causal Inference	—Unverified	0
Learning Representations for Counterfactual Inference	May 12, 2016	Causal Inferencecounterfactual	CodeCode Available	0
Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data	May 2, 2016	Causal Inference	CodeCode Available	0
Estimating Treatment Effects using Multiple Surrogates: The Role of the Surrogate Score and the Surrogate Index	Mar 30, 2016	Causal Inference	—Unverified	0
Scalable Linear Causal Inference for Irregularly Sampled Time Series with Long Range Dependencies	Mar 10, 2016	Causal InferenceTime Series	—Unverified	0
Causal inference for data-driven debugging and decision making in cloud computing	Mar 4, 2016	Causal InferenceCloud Computing	—Unverified	0
Recommendations as Treatments: Debiasing Learning and Evaluation	Feb 17, 2016	Causal InferenceRecommendation Systems	—Unverified	0
Private Causal Inference	Dec 17, 2015	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