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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 471–480 of 1722 papers

Title	Date	Tasks	Status	Hype
Causal hybrid modeling with double machine learning	Feb 20, 2024	Causal Inference	CodeCode Available	0
Integrating Active Learning in Causal Inference with Interference: A Novel Approach in Online Experiments	Feb 20, 2024	Active LearningCausal Inference	—Unverified	0
How causal inference concepts can guide research into the effects of climate on infectious diseases	Feb 19, 2024	Causal Inference	—Unverified	0
Graph Out-of-Distribution Generalization via Causal Intervention	Feb 18, 2024	Causal InferenceOut-of-Distribution Generalization	CodeCode Available	1
Manipulation Test for Multidimensional RDD	Feb 16, 2024	Causal Inference	—Unverified	0
Robust agents learn causal world models	Feb 16, 2024	Causal InferenceTransfer Learning	—Unverified	0
Local Projections Inference with High-Dimensional Covariates without Sparsity	Feb 12, 2024	Causal InferenceModel Selection	—Unverified	0
Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand	Feb 12, 2024	Causal InferenceDisentanglement	CodeCode Available	0
Navigating Market Turbulence: Insights from Causal Network Contagion Value at Risk	Feb 8, 2024	Causal InferenceManagement	—Unverified	0
Hyperparameter Tuning for Causal Inference with Double Machine Learning: A Simulation Study	Feb 7, 2024	AutoMLCausal 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