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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 1611–1620 of 1722 papers

Title	Date	Tasks	Status	Hype
Functional Generalized Empirical Likelihood Estimation for Conditional Moment Restrictions	Jul 11, 2022	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets	Jan 1, 2018	Causal Inferencecounterfactual	CodeCode Available	0
s-ID: Causal Effect Identification in a Sub-Population	Sep 5, 2023	Causal Inference	CodeCode Available	0
Measuring the Effect of Training Data on Deep Learning Predictions via Randomized Experiments	Jun 20, 2022	Causal Inference	CodeCode Available	0
Generalized Encouragement-Based Instrumental Variables for Counterfactual Regression	Aug 10, 2024	Causal Inferencecounterfactual	CodeCode Available	0
Measuring Variable Importance in Heterogeneous Treatment Effects with Confidence	Aug 23, 2024	Causal Inference	CodeCode Available	0
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference	Apr 30, 2024	Causal InferenceRecommendation Systems	CodeCode Available	0
Mechanism learning: Reverse causal inference in the presence of multiple unknown confounding through front-door causal bootstrapping	Oct 26, 2024	Causal Inference	CodeCode Available	0
Causal inference of brain connectivity from fMRI with ψ-Learning Incorporated Linear non-Gaussian Acyclic Model (ψ-LiNGAM)	Jun 16, 2020	Causal InferenceFunctional Connectivity	CodeCode Available	0
Causal Inference in Possibly Nonlinear Factor Models	Aug 31, 2020	Causal Inferencecounterfactual	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