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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 1181–1190 of 1722 papers

Title	Date	Tasks	Status	Hype
Kernel methods for long term dose response curves	Jan 13, 2022	Causal Inferencecounterfactual	—Unverified	0
Generalized Optimal Matching Methods for Causal Inference	Dec 26, 2016	Causal Inference	—Unverified	0
General Transportability of Soft Interventions: Completeness Results	Dec 1, 2020	Causal Inference	—Unverified	0
Generating High-Fidelity Privacy-Conscious Synthetic Patient Data for Causal Effect Estimation with Multiple Treatments	Sep 29, 2021	Causal Inference	—Unverified	0
Generating Synthetic Text Data to Evaluate Causal Inference Methods	Feb 10, 2021	Causal InferenceText Generation	—Unverified	0
Generative Intervention Models for Causal Perturbation Modeling	Nov 21, 2024	Causal Inference	—Unverified	0
Generator Identification for Linear SDEs with Additive and Multiplicative Noise	Oct 30, 2023	Causal Inference	—Unverified	0
Geometry-Aware Normalizing Wasserstein Flows for Optimal Causal Inference	Nov 30, 2023	Causal Inferenceparameter estimation	—Unverified	0
GP CaKe: Effective brain connectivity with causal kernels	May 16, 2017	Causal Inference	—Unverified	0
Granger Causality for Compressively Sensed Sparse Signals	Sep 23, 2022	Causal Inferencecompressed sensing	—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