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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 1651–1660 of 1722 papers

Title	Date	Tasks	Status	Hype
Comparison of meta-learners for estimating multi-valued treatment heterogeneous effects	May 29, 2022	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
Heterogeneous Treatment Effects in Panel Data	Jun 9, 2024	Causal Inferenceregression	CodeCode Available	0
Propensity score models are better when post-calibrated	Nov 2, 2022	Causal Inference	CodeCode Available	0
PROPHET: An Inferable Future Forecasting Benchmark with Causal Intervened Likelihood Estimation	Apr 2, 2025	ArticlesCausal Inference	CodeCode Available	0
Bayesian Topic Regression for Causal Inference	Sep 11, 2021	Causal Inferenceregression	CodeCode Available	0
An adaptive denoising recommendation algorithm for causal separation bias	Nov 15, 2023	Causal InferenceDenoising	CodeCode Available	0
Causal Inference with Hidden Mediators	Nov 4, 2021	Causal Inference	CodeCode Available	0
Causal Inference for Knowledge Graph based Recommendation	Dec 20, 2022	Causal InferenceCollaborative Filtering	CodeCode Available	0
High Dimensional Causal Inference with Variational Backdoor Adjustment	Oct 9, 2023	Causal InferenceVariational Inference	CodeCode Available	0
Model-Agnostic Covariate-Assisted Inference on Partially Identified Causal Effects	Oct 12, 2023	Causal Inferencevalid	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