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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 1311–1320 of 1722 papers

Title	Date	Tasks	Status	Hype
Learning Invariant Causal Mechanism from Vision-Language Models	May 24, 2024	Causal InferenceDecision Making	—Unverified	0
Learning linear structural equation models in polynomial time and sample complexity	Jul 15, 2017	Causal InferenceComputational Efficiency	—Unverified	0
Learning Optimal Fair Policies	Sep 6, 2018	Causal InferenceDecision Making	—Unverified	0
Learning Quadratic Variance Function (QVF) DAG models via OverDispersion Scoring (ODS)	Apr 28, 2017	Causal Inference	—Unverified	0
Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery	Jan 25, 2022	Causal InferenceFairness	—Unverified	0
Learning Structural Causal Models from Ordering: Identifiable Flow Models	Dec 13, 2024	Causal Inferencecounterfactual	—Unverified	0
The Amenability Framework: Rethinking Causal Ordering Without Estimating Causal Effects	Jun 25, 2022	Causal InferenceDecision Making	—Unverified	0
Learning Weighted Representations for Generalization Across Designs	Feb 23, 2018	Causal InferenceDomain Adaptation	—Unverified	0
Lee Bounds with a Continuous Treatment in Sample Selection	Nov 6, 2024	Causal InferenceSelection bias	—Unverified	0
Leveraging Causal Inference for Explainable Automatic Program Repair	May 26, 2022	Bug fixingCausal Inference	—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