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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 611–620 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Benign-Overfitting in Conditional Average Treatment Effect Prediction with Linear Regression	Feb 10, 2022	Causal Inferenceregression	—Unverified	0	0
An Automated Approach to Causal Inference in Discrete Settings	Sep 28, 2021	Causal Inference	—Unverified	0	0
Adaptive Multi-Source Causal Inference	May 31, 2021	Causal InferenceTransfer Learning	—Unverified	0	0
A causal inference approach of monosynapses from spike trains	May 5, 2024	Causal InferenceFunctional Connectivity	—Unverified	0	0
Transfer Learning for Individual Treatment Effect Estimation	Oct 1, 2022	Causal Inferencecounterfactual	—Unverified	0	0
Benchmarking Causal Study to Interpret Large Language Models for Source Code	Aug 23, 2023	BenchmarkingCausal Inference	—Unverified	0	0
Causal knowledge graph analysis identifies adverse drug effects	May 11, 2025	Causal InferenceKnowledge Graphs	—Unverified	0	0
Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation	Jul 11, 2023	BenchmarkingCausal Discovery	—Unverified	0	0
Analyzing Behaviors of Mixed Traffic via Reinforcement Learning at Unsignalized Intersections	Nov 21, 2023	Causal InferenceManagement	—Unverified	0	0
Causality in the Can: Diet Coke's Impact on Fatness	May 17, 2024	Causal Inferencecounterfactual	—Unverified	0	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