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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 1521–1530 of 1722 papers

Title	Date	Tasks	Status	Hype
When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks	Feb 9, 2019	Causal InferenceVisual Reasoning	CodeCode Available	0
Fair Decisions Despite Imperfect Predictions	Feb 8, 2019	Causal InferenceDecision Making	CodeCode Available	0
On L_2-consistency of nearest neighbor matching	Feb 6, 2019	Causal InferenceDomain Adaptation	—Unverified	0
Causal Effect Identification from Multiple Incomplete Data Sources: A General Search-based Approach	Feb 4, 2019	Causal IdentificationCausal Inference	—Unverified	0
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders	Feb 1, 2019	Causal InferenceTime Series	CodeCode Available	0
Causal Discovery with a Mixture of DAGs	Jan 28, 2019	Causal DiscoveryCausal Inference	—Unverified	0
Causal Mediation Analysis Leveraging Multiple Types of Summary Statistics Data	Jan 24, 2019	Causal Inference	—Unverified	0
Shared Causal Paths underlying Alzheimer's dementia and Type 2 Diabetes	Jan 16, 2019	Causal InferenceVocal Bursts Type Prediction	—Unverified	0
Variable Importance Clouds: A Way to Explore Variable Importance for the Set of Good Models	Jan 10, 2019	Causal Inferenceimage-classification	CodeCode Available	0
Estimating Buildings' Parameters over Time Including Prior Knowledge	Jan 9, 2019	Causal Inferenceparameter estimation	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