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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 1531–1540 of 1722 papers

Title	Date	Tasks	Status	Hype
Estimating Individual Treatment Effects using Non-Parametric Regression Models: a Review	Sep 14, 2020	Causal InferenceModel Selection	CodeCode Available	0
A Fundamental Probabilistic Fuzzy Logic Framework Suitable for Causal Reasoning	May 30, 2022	AttributeCausal Inference	CodeCode Available	0
Causally motivated Shortcut Removal Using Auxiliary Labels	May 13, 2021	Causal InferenceDisentanglement	CodeCode Available	0
Leveraging text data for causal inference using electronic health records	Jun 9, 2023	Causal InferenceImputation	CodeCode Available	0
Lifted Causal Inference in Relational Domains	Mar 15, 2024	Causal Inference	CodeCode Available	0
Variance Minimization in the Wasserstein Space for Invariant Causal Prediction	Oct 13, 2021	Causal DiscoveryCausal Inference	CodeCode Available	0
Causally Denoise Word Embeddings Using Half-Sibling Regression	Nov 24, 2019	Causal Inferenceregression	CodeCode Available	0
Paths to Causality: Finding Informative Subgraphs Within Knowledge Graphs for Knowledge-Based Causal Discovery	Jun 10, 2025	Causal DiscoveryCausal Inference	CodeCode Available	0
Causality-oriented robustness: exploiting general noise interventions	Jul 18, 2023	Causal InferenceDomain Adaptation	CodeCode Available	0
Weather2vec: Representation Learning for Causal Inference with Non-Local Confounding in Air Pollution and Climate Studies	Sep 25, 2022	Causal InferenceRepresentation Learning	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