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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 461–470 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
On the Mechanistic Interpretability of Neural Networks for Causality in Bio-statistics	May 1, 2025	Causal Inference	CodeCode Available	0	5
On the Out-of-Distribution Generalization of Self-Supervised Learning	May 22, 2025	Causal InferenceOut-of-Distribution Generalization	CodeCode Available	0	5
Adapting Neural Networks for the Estimation of Treatment Effects	Jun 5, 2019	Causal Inference	CodeCode Available	0	5
Optimal transport weights for causal inference	Sep 5, 2021	Causal Inference	CodeCode Available	0	5
Bayesian Topic Regression for Causal Inference	Sep 11, 2021	Causal Inferenceregression	CodeCode Available	0	5
Combinatorial Causal Bandits	Jun 4, 2022	Causal Inference	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
Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid	Sep 27, 2021	Causal InferenceDesign Synthesis	CodeCode Available	0	5
Causality for Machine Learning	Nov 24, 2019	BIG-bench Machine LearningCausal Inference	CodeCode Available	0	5
Challenges of Using Text Classifiers for Causal Inference	Oct 1, 2018	Causal InferenceDecision Making	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