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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 1521–1530 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Causal Rule Forest: Toward Interpretable and Precise Treatment Effect Estimation	Aug 27, 2024	Causal Inference	—Unverified	0	0
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect	Oct 16, 2017	Causal InferenceSubgroup Discovery	—Unverified	0	0
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach	Apr 25, 2023	Causal InferenceDecision Making	—Unverified	0	0
Causal Structure Recovery of Linear Dynamical Systems: An FFT based Approach	Sep 5, 2023	Causal InferenceGraph Reconstruction	—Unverified	0	0
Causal Triple Attention Time Series Forecasting	Sep 29, 2021	Causal InferenceTime Series	—Unverified	0	0
Analyzing User Characteristics of Hate Speech Spreaders on Social Media	Oct 24, 2023	Causal InferenceSelection bias	—Unverified	0	0
Causal versions of Maximum Entropy and Principle of Insufficient Reason	Feb 7, 2021	Causal Inference	—Unverified	0	0
Cause-Effect Deep Information Bottleneck For Systematically Missing Covariates	Jul 6, 2018	Causal Inference	—Unverified	0	0
Cause-effect inference through spectral independence in linear dynamical systems: theoretical foundations	Oct 29, 2021	Causal DiscoveryCausal Inference	—Unverified	0	0
Causes of evolutionary divergence in prostate cancer	Mar 17, 2025	Causal Inference	—Unverified	0	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