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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 1351–1360 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Causal and anti-causal learning in pattern recognition for neuroimaging	Dec 15, 2015	Causal Inference	—Unverified	0	0
Causal and Counterfactual Views of Missing Data Models	Oct 11, 2022	Causal IdentificationCausal Inference	—Unverified	0	0
CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing	May 4, 2023	Causal InferenceDisentanglement	—Unverified	0	0
Causal-Aware Intelligent QoE Optimization for VR Interaction with Adaptive Keyframe Extraction	Jun 24, 2025	Causal InferenceCPU	—Unverified	0	0
Causal Bandits: Learning Good Interventions via Causal Inference	Jun 10, 2016	Causal Inference	—Unverified	0	0
Causal Bayesian Optimization	May 24, 2020	Bayesian OptimizationCausal Inference	—Unverified	0	0
CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervision	Jul 21, 2021	Causal Inference	—Unverified	0	0
Causal bootstrapping	Oct 21, 2019	BIG-bench Machine LearningCausal Inference	—Unverified	0	0
CausalCellSegmenter: Causal Inference inspired Diversified Aggregation Convolution for Pathology Image Segmentation	Mar 10, 2024	Causal InferenceImage Segmentation	—Unverified	0	0
Causal Claims in Economics	Jan 12, 2025	Causal InferenceKnowledge Graphs	—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