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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 1271–1280 of 1722 papers

Title	Date	Tasks	Status	Hype
A Review of Generalizability and Transportability	Feb 23, 2021	Causal Inference	—Unverified	0
SBI: A Simulation-Based Test of Identifiability for Bayesian Causal Inference	Feb 23, 2021	Causal InferenceExperimental Design	—Unverified	0
Quantum Entropic Causal Inference	Feb 23, 2021	Causal Inference	—Unverified	0
Towards Causal Representation Learning	Feb 22, 2021	BIG-bench Machine LearningCausal Inference	—Unverified	0
Causal Mediation Analysis with Hidden Confounders	Feb 21, 2021	Causal InferenceFairness	—Unverified	0
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models	Feb 20, 2021	Causal Inference	CodeCode Available	0
Adaptive Doubly Robust Estimator from Non-stationary Logging Policy under a Convergence of Average Probability	Feb 17, 2021	Causal InferenceCounterfactual Inference	—Unverified	0
Causal Estimation with Functional Confounders	Feb 17, 2021	Causal Inference	—Unverified	0
Do-calculus enables estimation of causal effects in partially observed biomolecular pathways	Feb 12, 2021	Causal Inference	CodeCode Available	0
A Critical Look at the Consistency of Causal Estimation With Deep Latent Variable Models	Feb 12, 2021	Causal InferenceOpen-Ended Question Answering	—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