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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 671–680 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy	Jul 6, 2021	Causal InferenceMatrix Completion	—Unverified	0	0
Causal Inference with Conditional Instruments using Deep Generative Models	Nov 29, 2022	Causal Inference	—Unverified	0	0
Balanced Linear Contextual Bandits	Dec 15, 2018	Causal InferenceMulti-Armed Bandits	—Unverified	0	0
A Computational Framework for Solving Nonlinear Binary OptimizationProblems in Robust Causal Inference	Dec 22, 2020	Causal InferenceDecision Making	—Unverified	0	0
Action needed to make carbon offsets from tropical forest conservation work for climate change mitigation	Jan 5, 2023	AttributeCausal Inference	—Unverified	0	0
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder	Oct 3, 2023	Causal Inference	—Unverified	0	0
Causal Inference with Complex Treatments: A Survey	Jul 19, 2024	Causal InferenceDecision Making	—Unverified	0	0
Axiomatization of Interventional Probability Distributions	May 8, 2023	Causal Inference	—Unverified	0	0
Causal inference with Bayes rule	Oct 2, 2019	Causal Inference	—Unverified	0	0
A Way to Synthetic Triple Difference	Sep 18, 2024	Causal Inference	—Unverified	0	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