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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 1031–1040 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
T2TD: Text-3D Generation Model based on Prior Knowledge Guidance	May 25, 2023	3D Generation3D Reconstruction	—Unverified	0	0
Targeted Data Fusion for Causal Survival Analysis Under Distribution Shift	Jan 30, 2025	Causal InferenceData Integration	—Unverified	0	0
Targeted VAE: Structured Inference and Targeted Learning for Causal Parameter Estimation	Sep 28, 2020	Causal Inferencecounterfactual	—Unverified	0	0
Targeting Learning: Robust Statistics for Reproducible Research	Jun 12, 2020	Causal InferenceSurvival Analysis	—Unverified	0	0
Task-specific experimental design for treatment effect estimation	Jun 8, 2023	Causal InferenceExperimental Design	—Unverified	0	0
TC-LLaVA: Rethinking the Transfer from Image to Video Understanding with Temporal Considerations	Sep 5, 2024	Causal InferencePosition	—Unverified	0	0
T-CPDL: A Temporal Causal Probabilistic Description Logic for Developing Logic-RAG Agent	Jun 23, 2025	Causal InferenceDecision Making	—Unverified	0	0
Incorporating Causal Effects into Deep Learning Predictions on EHR Data	Nov 11, 2020	Causal InferenceDeep Learning	—Unverified	0	0
Telling cause from effect in deterministic linear dynamical systems	Mar 4, 2015	Causal DiscoveryCausal Inference	—Unverified	0	0
Temporal Inference with Finite Factored Sets	Sep 23, 2021	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