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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 551–560 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
A Neural Framework for Generalized Causal Sensitivity Analysis	Nov 27, 2023	Causal InferenceSensitivity	CodeCode Available	0	5
COLD: Causal reasOning in cLosed Daily activities	Nov 29, 2024	Causal InferenceCommonsense Causal Reasoning	CodeCode Available	0	5
Comparison between instrumental variable and mediation-based methods for reconstructing causal gene networks in yeast	Oct 14, 2020	Causal Inference	CodeCode Available	0	5
Counterfactual Fairness	Mar 20, 2017	BIG-bench Machine LearningCausal Inference	CodeCode Available	0	5
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits	Dec 1, 2019	Causal InferenceModel Selection	CodeCode Available	0	5
Debiasing Recommendation by Learning Identifiable Latent Confounders	Feb 10, 2023	Causal Inferencecounterfactual	CodeCode Available	0	5
Double Machine Learning for Causal Inference under Shared-State Interference	Apr 10, 2025	Causal InferenceRecommendation Systems	CodeCode Available	0	5
Detecting hidden confounding in observational data using multiple environments	May 27, 2022	Causal Inference	CodeCode Available	0	5
Facial Action Unit Detection by Adaptively Constraining Self-Attention and Causally Deconfounding Sample	Oct 2, 2024	Action Unit DetectionCausal Inference	CodeCode Available	0	5
Learning sources of variability from high-dimensional observational studies	Jul 26, 2023	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