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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 951–960 of 1722 papers

Title	Date	Tasks	Status	Hype
A Mixing Time Lower Bound for a Simplified Version of BART	Oct 17, 2022	Causal Inferenceregression	—Unverified	0
Fair Effect Attribution in Parallel Online Experiments	Oct 15, 2022	AttributeCausal Inference	—Unverified	0
Distributionally Robust Causal Inference with Observational Data	Oct 15, 2022	Causal InferenceSensitivity	—Unverified	0
On the Identifiability and Estimation of Causal Location-Scale Noise Models	Oct 13, 2022	Causal DiscoveryCausal Inference	CodeCode Available	0
Developing a general-purpose clinical language inference model from a large corpus of clinical notes	Oct 12, 2022	Causal InferenceDecoder	—Unverified	0
Sample Constrained Treatment Effect Estimation	Oct 12, 2022	Causal Inference	CodeCode Available	0
Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders	Oct 11, 2022	Causal Inference	CodeCode Available	0
Causal and Counterfactual Views of Missing Data Models	Oct 11, 2022	Causal IdentificationCausal Inference	—Unverified	0
DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning	Oct 10, 2022	Causal InferenceDeep Learning	CodeCode Available	0
LLMEffiChecker: Understanding and Testing Efficiency Degradation of Large Language Models	Oct 7, 2022	Causal InferenceMachine Translation	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