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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 1461–1470 of 1722 papers

Title	Date	Tasks	Status	Hype
Doubly-Valid/Doubly-Sharp Sensitivity Analysis for Causal Inference with Unmeasured Confounding	Dec 21, 2021	Causal InferenceSensitivity	CodeCode Available	0
Choice Set Confounding in Discrete Choice	May 17, 2021	Causal InferenceDiscrete Choice Models	CodeCode Available	0
Challenges of Using Text Classifiers for Causal Inference	Oct 1, 2018	Causal InferenceDecision Making	CodeCode Available	0
CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data Assimilation	Apr 10, 2024	Causal InferenceState Estimation	CodeCode Available	0
RNN-based counterfactual prediction, with an application to homestead policy and public schooling	Dec 10, 2017	Causal Inferencecounterfactual	CodeCode Available	0
Causal Campbell-Goodhart's law and Reinforcement Learning	Nov 2, 2020	Causal InferenceDecision Making	CodeCode Available	0
Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door Adjustment	Mar 5, 2024	Causal Inferencecounterfactual	CodeCode Available	0
Optimal Estimation of Generalized Average Treatment Effects using Kernel Optimal Matching	Aug 13, 2019	Causal Inference	CodeCode Available	0
Causal-StoNet: Causal Inference for High-Dimensional Complex Data	Mar 27, 2024	Causal InferenceEconometrics	CodeCode Available	0
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects Estimation	May 25, 2023	Causal Inferencecounterfactual	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