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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 591–600 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
An Efficient Doubly-Robust Test for the Kernel Treatment Effect	Apr 26, 2023	Causal Inferencevalid	—Unverified	0	0
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series	Mar 4, 2024	Causal InferenceTime Series	—Unverified	0	0
A Causal Inference Framework for Data Rich Environments	Apr 2, 2025	Causal Inferencecounterfactual	—Unverified	0	0
Causal modelling without introducing counterfactuals or abstract distributions	Jul 24, 2024	Causal Inferencecounterfactual	—Unverified	0	0
Beyond Patterns: Harnessing Causal Logic for Autonomous Driving Trajectory Prediction	May 11, 2025	Autonomous DrivingCausal Inference	—Unverified	0	0
Causal Model Analysis using Collider v-structure with Negative Percentage Mapping	Sep 16, 2015	Causal Inference	—Unverified	0	0
Beyond Flatland: A Geometric Take on Matching Methods for Treatment Effect Estimation	Sep 9, 2024	Causal Inference	—Unverified	0	0
Beyond Correlation: Towards Causal Large Language Model Agents in Biomedicine	May 22, 2025	Causal InferenceDrug Discovery	—Unverified	0	0
Causal Mediation Analysis with Hidden Confounders	Feb 21, 2021	Causal InferenceFairness	—Unverified	0	0
Causal Mediation Analysis Leveraging Multiple Types of Summary Statistics Data	Jan 24, 2019	Causal Inference	—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