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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 1451–1460 of 1722 papers

Title	Date	Tasks	Status	Hype
Large Dimensional Latent Factor Modeling with Missing Observations and Applications to Causal Inference	Oct 18, 2019	Causal Inferencecounterfactual	—Unverified	0
Masked Gradient-Based Causal Structure Learning	Oct 18, 2019	Causal DiscoveryCausal Inference	CodeCode Available	1
Bimodular continuous attractor neural networks with static and moving stimuli	Oct 16, 2019	Causal Inference	—Unverified	0
Optimising Individual-Treatment-Effect Using Bandits	Oct 16, 2019	Causal InferenceMarketing	CodeCode Available	0
The Case for Evaluating Causal Models Using Interventional Measures and Empirical Data	Oct 11, 2019	Causal InferenceFairness	—Unverified	0
Comment on "Blessings of Multiple Causes"	Oct 11, 2019	Causal Inferencevalid	—Unverified	0
Estimating Transfer Entropy via Copula Entropy	Oct 10, 2019	Causal DiscoveryCausal Inference	CodeCode Available	1
Kernel-based Approach to Handle Mixed Data for Inferring Causal Graphs	Oct 7, 2019	Causal Inference	—Unverified	0
Donor's Deferral and Return Behavior: Partial Identification from a Regression Discontinuity Design with Manipulation	Oct 4, 2019	Causal Inferenceregression	—Unverified	0
Spike-based causal inference for weight alignment	Oct 3, 2019	Causal InferenceEconometrics	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