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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 551–560 of 1722 papers

Title	Date	Tasks	Status	Hype
Variable Selection in Maximum Mean Discrepancy for Interpretable Distribution Comparison	Nov 2, 2023	Causal InferenceRelevance Detection	—Unverified	0
TRIALSCOPE: A Unifying Causal Framework for Scaling Real-World Evidence Generation with Biomedical Language Models	Nov 2, 2023	Causal InferenceDenoising	—Unverified	0
Text-Transport: Toward Learning Causal Effects of Natural Language	Oct 31, 2023	AttributeCausal Inference	CodeCode Available	0
Generator Identification for Linear SDEs with Additive and Multiplicative Noise	Oct 30, 2023	Causal Inference	—Unverified	0
Causal Modeling with Stationary Diffusions	Oct 26, 2023	Causal Inference	CodeCode Available	1
Causality-Inspired Fair Representation Learning for Multimodal Recommendation	Oct 26, 2023	AttributeCausal Inference	CodeCode Available	1
Local Discovery by Partitioning: Polynomial-Time Causal Discovery Around Exposure-Outcome Pairs	Oct 25, 2023	Causal DiscoveryCausal Inference	CodeCode Available	0
Causal Q-Aggregation for CATE Model Selection	Oct 25, 2023	Causal InferenceDecision Making	—Unverified	0
CATE Lasso: Conditional Average Treatment Effect Estimation with High-Dimensional Linear Regression	Oct 25, 2023	Causal Inferenceregression	—Unverified	0
Analyzing User Characteristics of Hate Speech Spreaders on Social Media	Oct 24, 2023	Causal InferenceSelection bias	—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