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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 1091–1100 of 1722 papers

Title	Date	Tasks	Status	Hype
Private measurement of nonlinear correlations between data hosted across multiple parties	Oct 19, 2021	Causal Inference	—Unverified	0
Counterfactual Debiasing Inference for Compositional Action Recognition	Oct 17, 2021	Action RecognitionCausal Inference	CodeCode Available	1
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang	Oct 16, 2021	Causal DiscoveryCausal Inference	—Unverified	0
Identifying Causal Influences on Publication Trends and Behavior: A Case Study of the Computational Linguistics Community	Oct 15, 2021	Causal Inference	—Unverified	0
Causal Identification with Additive Noise Models: Quantifying the Effect of Noise	Oct 15, 2021	Causal DiscoveryCausal Identification	—Unverified	0
Variance Minimization in the Wasserstein Space for Invariant Causal Prediction	Oct 13, 2021	Causal DiscoveryCausal Inference	CodeCode Available	0
Causal Discovery from Conditionally Stationary Time Series	Oct 12, 2021	Causal DiscoveryCausal Inference	—Unverified	0
Density-based interpretable hypercube region partitioning for mixed numeric and categorical data	Oct 11, 2021	Causal Inference	—Unverified	0
β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap	Oct 11, 2021	Causal Inference	—Unverified	0
High-dimensional Inference for Dynamic Treatment Effects	Oct 10, 2021	Causal InferenceVocal Bursts Intensity Prediction	—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