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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 1421–1430 of 1722 papers

Title	Date	Tasks	Status	Hype
On the Out-of-Distribution Generalization of Self-Supervised Learning	May 22, 2025	Causal InferenceOut-of-Distribution Generalization	CodeCode Available	0
Kernel-based estimators for functional causal effects	Mar 6, 2025	Causal Inference	CodeCode Available	0
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders	Oct 11, 2022	Causal Inference	CodeCode Available	0
Conditional Cross-Design Synthesis Estimators for Generalizability in Medicaid	Sep 27, 2021	Causal InferenceDesign Synthesis	CodeCode Available	0
Compositional Probabilistic and Causal Inference using Tractable Circuit Models	Apr 17, 2023	Causal Inference	CodeCode Available	0
Comparison between instrumental variable and mediation-based methods for reconstructing causal gene networks in yeast	Oct 14, 2020	Causal Inference	CodeCode Available	0
Sequential Kernel Embedding for Mediated and Time-Varying Dose Response Curves	Nov 6, 2021	Causal Inferencecounterfactual	CodeCode Available	0
Tangential Wasserstein Projections	Jul 29, 2022	Causal Inference	CodeCode Available	0
χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid Domains	Aug 14, 2024	Causal Inference	CodeCode Available	0
Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical Systems	Oct 30, 2024	Causal DiscoveryCausal Inference	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