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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 1481–1490 of 1722 papers

Title	Date	Tasks	Status	Hype
Efficient and accurate causal inference with hidden confounders from genome-transcriptome variation data	Apr 17, 2017	Causal Inference	CodeCode Available	0
Combining Interventional and Observational Data Using Causal Reductions	Mar 8, 2021	Causal Inference	CodeCode Available	0
Learning Conditional Instrumental Variable Representation for Causal Effect Estimation	Jun 21, 2023	Causal InferenceRepresentation Learning	CodeCode Available	0
Robust detection and attribution of climate change under interventions	Dec 9, 2022	Causal InferenceChange Detection	CodeCode Available	0
Using representation balancing to learn conditional-average dose responses from clustered data	Sep 7, 2023	BenchmarkingCausal Inference	CodeCode Available	0
Targeting customers under response-dependent costs	Mar 13, 2020	Causal InferenceMarketing	CodeCode Available	0
Causal affect prediction model using a facial image sequence	Jul 8, 2021	Causal InferenceFacial Expression Recognition	CodeCode Available	0
CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual Inference	Jan 27, 2025	Causal Inferencecounterfactual	CodeCode Available	0
Causal Expectation-Maximisation	Nov 4, 2020	Causal Inferencecounterfactual	CodeCode Available	0
Can We Validate Counterfactual Estimations in the Presence of General Network Interference?	Feb 3, 2025	Causal Inferencecounterfactual	CodeCode Available	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