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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 601–610 of 1722 papers

Title	Date	Tasks	Status	Hype
Using representation balancing to learn conditional-average dose responses from clustered data	Sep 7, 2023	BenchmarkingCausal Inference	CodeCode Available	0
Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Length	Sep 5, 2023	Causal InferenceModel Selection	CodeCode Available	0
Causal Structure Recovery of Linear Dynamical Systems: An FFT based Approach	Sep 5, 2023	Causal InferenceGraph Reconstruction	—Unverified	0
s-ID: Causal Effect Identification in a Sub-Population	Sep 5, 2023	Causal Inference	CodeCode Available	0
INTAGS: Interactive Agent-Guided Simulation	Sep 4, 2023	Algorithmic TradingCausal Inference	—Unverified	0
Measuring, Interpreting, and Improving Fairness of Algorithms using Causal Inference and Randomized Experiments	Sep 4, 2023	Causal InferenceFairness	—Unverified	0
Emoji Promotes Developer Participation and Issue Resolution on GitHub	Aug 30, 2023	Causal Inference	—Unverified	0
Woolf et als GWAS by subtraction is not useful for cross-generational Mendelian randomization studies	Aug 28, 2023	Causal Inference	—Unverified	0
Machine Unlearning for Causal Inference	Aug 24, 2023	Causal InferenceMachine Unlearning	—Unverified	0
Causal Parrots: Large Language Models May Talk Causality But Are Not Causal	Aug 24, 2023	Causal Inference	CodeCode Available	1

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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