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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 691–700 of 1722 papers

Title	Date	Tasks	Status	Hype
Reinterpreting causal discovery as the task of predicting unobserved joint statistics	May 11, 2023	Causal DiscoveryCausal Inference	—Unverified	0
Integrating Nearest Neighbors with Neural Network Models for Treatment Effect Estimation	May 11, 2023	Causal Inference	—Unverified	0
COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective	May 9, 2023	Causal InferenceCoLA	CodeCode Available	1
Axiomatization of Interventional Probability Distributions	May 8, 2023	Causal Inference	—Unverified	0
The Fundamental Limits of Structure-Agnostic Functional Estimation	May 6, 2023	Causal Inference	—Unverified	0
Causal Discovery with Stage Variables for Health Time Series	May 5, 2023	Causal DiscoveryCausal Inference	—Unverified	0
String Diagrams with Factorized Densities	May 4, 2023	Causal InferenceProbabilistic Programming	—Unverified	0
Understand Waiting Time in Transaction Fee Mechanism: An Interdisciplinary Perspective	May 4, 2023	Causal InferenceComputer Security	CodeCode Available	0
CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing	May 4, 2023	Causal InferenceDisentanglement	—Unverified	0
Efficient estimation of weighted cumulative treatment effects by double/debiased machine learning	May 3, 2023	Causal Inference	—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