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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 1291–1300 of 1722 papers

Title	Date	Tasks	Status	Hype
Policy Analysis using Synthetic Controls in Continuous-Time	Feb 2, 2021	Causal Inferencecounterfactual	CodeCode Available	0
Customer Price Sensitivities in Competitive Automobile Insurance Markets	Jan 21, 2021	Causal Inferencecounterfactual	—Unverified	0
Intact-VAE: Estimating Treatment Effects under Unobserved Confounding	Jan 17, 2021	Causal InferenceRepresentation Learning	—Unverified	0
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification	Jan 11, 2021	Causal Emotion EntailmentCausal Inference	CodeCode Available	0
Entropic Causal Inference: Identifiability and Finite Sample Results	Jan 10, 2021	Causal IdentificationCausal Inference	—Unverified	0
A design of human-like robust AI machines in object identification	Jan 7, 2021	Causal InferenceCommon Sense Reasoning	—Unverified	0
The Value Added of Machine Learning to Causal Inference: Evidence from Revisited Studies	Jan 4, 2021	BIG-bench Machine LearningCausal Inference	—Unverified	0
Counterfactual Thinking for Long-tailed Information Extraction	Jan 1, 2021	Causal Inferencecounterfactual	—Unverified	0
Invariant Representations for Reinforcement Learning without Reconstruction	Jan 1, 2021	Causal InferenceMuJoCo	—Unverified	0
Variational Deterministic Uncertainty Quantification	Jan 1, 2021	Causal Inferenceregression	—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