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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 1511–1520 of 1722 papers

Title	Date	Tasks	Status	Hype
Learning Representations of Instruments for Partial Identification of Treatment Effects	Oct 11, 2024	Causal InferenceDecision Making	CodeCode Available	0
Equivariance Allows Handling Multiple Nuisance Variables When Analyzing Pooled Neuroimaging Datasets	Mar 29, 2022	Causal InferenceDomain Adaptation	CodeCode Available	0
A Survey on Causal Representation Learning and Future Work for Medical Image Analysis	Oct 28, 2022	Causal InferenceMedical Image Analysis	CodeCode Available	0
Learning sources of variability from high-dimensional observational studies	Jul 26, 2023	Causal Inference	CodeCode Available	0
Sample Constrained Treatment Effect Estimation	Oct 12, 2022	Causal Inference	CodeCode Available	0
Estimating Buildings' Parameters over Time Including Prior Knowledge	Jan 9, 2019	Causal Inferenceparameter estimation	CodeCode Available	0
Learning the Causal Structure of Networked Dynamical Systems under Latent Nodes and Structured Noise	Dec 10, 2023	Causal InferenceTime Series	CodeCode Available	0
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies	Dec 19, 2021	Causal Inference	CodeCode Available	0
A Survey on Causal Inference	Feb 5, 2020	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
Causal prediction models for medication safety monitoring: The diagnosis of vancomycin-induced acute kidney injury	Nov 15, 2023	Causal 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