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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 191–200 of 1722 papers

Title	Date	Tasks	Status	Hype
Learning Invariant Representations for Reinforcement Learning without Reconstruction	Jun 18, 2020	Causal InferenceMuJoCo	CodeCode Available	1
An End-to-End Framework to Identify Pathogenic Social Media Accounts on Twitter	May 4, 2019	Causal Inference	—Unverified	0
An End-to-End Framework for Marketing Effectiveness Optimization under Budget Constraint	Feb 9, 2023	Causal InferenceMarketing	—Unverified	0
ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects	Nov 12, 2021	BenchmarkingCausal Inference	—Unverified	0
An Empirical Comparison of Weak-IV-Robust Procedures in Just-Identified Models	Jun 22, 2025	Causal Inference	—Unverified	0
An Efficient Doubly-Robust Test for the Kernel Treatment Effect	Apr 26, 2023	Causal Inferencevalid	—Unverified	0
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series	Mar 4, 2024	Causal InferenceTime Series	—Unverified	0
A Causal Inference Framework for Data Rich Environments	Apr 2, 2025	Causal Inferencecounterfactual	—Unverified	0
A causal inference approach of monosynapses from spike trains	May 5, 2024	Causal InferenceFunctional Connectivity	—Unverified	0
Ancestral Instrument Method for Causal Inference without Complete Knowledge	Jan 11, 2022	Causal Inferencevalid	—Unverified	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