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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 431–440 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Conditional Generative Models are Sufficient to Sample from Any Causal Effect Estimand	Feb 12, 2024	Causal InferenceDisentanglement	CodeCode Available	0	5
Learning Treatment Effects in Panels with General Intervention Patterns	Jun 5, 2021	Causal Inference	CodeCode Available	0	5
Confounding Feature Acquisition for Causal Effect Estimation	Nov 17, 2020	Causal Inference	CodeCode Available	0	5
Lifted Causal Inference in Relational Domains	Mar 15, 2024	Causal Inference	CodeCode Available	0	5
An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal Inference	Jun 2, 2019	BIG-bench Machine LearningCausal Inference	CodeCode Available	0	5
Causal Inference with Cocycles	May 22, 2024	Causal Inferencecounterfactual	CodeCode Available	0	5
Localized Debiased Machine Learning: Efficient Inference on Quantile Treatment Effects and Beyond	Dec 30, 2019	BIG-bench Machine LearningCausal Inference	CodeCode Available	0	5
Local Linear Forests	Jul 30, 2018	Causal InferenceHeterogeneous Treatment Effect Estimation	CodeCode Available	0	5
Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid	Sep 27, 2021	Causal InferenceDesign Synthesis	CodeCode Available	0	5
Consistent Estimation of Propensity Score Functions with Oversampled Exposed Subjects	May 20, 2018	Causal Inference	CodeCode Available	0	5

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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