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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
Causal Inference Using Tractable Circuits	Feb 7, 2022	Causal Inference	—Unverified	0
Deep End-to-end Causal Inference	Feb 4, 2022	Causal DiscoveryCausal Inference	—Unverified	0
Causal Inference Through the Structural Causal Marginal Problem	Feb 2, 2022	Causal Inferencecounterfactual	CodeCode Available	0
Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts	Feb 2, 2022	Causal Inference	—Unverified	0
Heterogeneous Peer Effects in the Linear Threshold Model	Jan 27, 2022	Causal Inferencemodel	CodeCode Available	0
Promises and Challenges of Causality for Ethical Machine Learning	Jan 26, 2022	BIG-bench Machine LearningCausal Inference	—Unverified	0
Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects	Jan 26, 2022	Causal Inference	—Unverified	0
Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery	Jan 25, 2022	Causal InferenceFairness	—Unverified	0
Symbiotic bacterial network structure involved in carbon and nitrogen metabolism of wood-utilizing insect larvae	Jan 24, 2022	Causal Inference	—Unverified	0
Time-Series K-means in Causal Inference and Mechanism Clustering for Financial Data	Jan 24, 2022	Causal InferenceClustering	—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