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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 711–720 of 1722 papers

Title	Date	Tasks	Status	Hype
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions	Jun 25, 2023	Causal Inference	—Unverified	0
Discovering Context Specific Causal Relationships	Aug 20, 2018	Causal InferenceDecision Making	—Unverified	0
Disentangled Latent Representation Learning for Tackling the Confounding M-Bias Problem in Causal Inference	Dec 8, 2023	Causal InferenceRepresentation Learning	—Unverified	0
Disentangled Representation Learning for Causal Inference with Instruments	Dec 5, 2024	Causal InferenceRepresentation Learning	—Unverified	0
Causal Inference by Stochastic Complexity	Feb 22, 2017	Causal Inference	—Unverified	0
Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference	Sep 21, 2020	Causal Inference	—Unverified	0
Comment on "Blessings of Multiple Causes"	Oct 11, 2019	Causal Inferencevalid	—Unverified	0
Combining Offline Causal Inference and Online Bandit Learning for Data Driven Decision	Jan 16, 2020	Causal Inference	—Unverified	0
A novel approach to the relationships between data features -- based on comprehensive examination of mathematical, technological, and causal methodology	Feb 20, 2025	Causal Inferencecounterfactual	—Unverified	0
A Causal Lens for Controllable Text Generation	Jan 22, 2022	AttributeCausal 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