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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 391–400 of 1722 papers

Title	Date	Tasks	Status	Hype
Simultaneous Inference for Local Structural Parameters with Random Forests	May 13, 2024	Causal Inferenceregression	—Unverified	0
Estimating Direct and Indirect Causal Effects of Spatiotemporal Interventions in Presence of Spatial Interference	May 13, 2024	Causal Inference	—Unverified	0
From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy	May 12, 2024	Causal Inferencecounterfactual	—Unverified	0
Causal Inference from Slowly Varying Nonstationary Processes	May 11, 2024	Causal IdentificationCausal Inference	—Unverified	0
Semi-supervised Anomaly Detection via Adaptive Reinforcement Learning-Enabled Method with Causal Inference for Sensor Signals	May 11, 2024	Anomaly DetectionCausal Inference	CodeCode Available	0
Causal inference approach to appraise long-term effects of maintenance policy on functional performance of asphalt pavements	May 6, 2024	Causal Inference	—Unverified	0
Out-of-Distribution Adaptation in Offline RL: Counterfactual Reasoning via Causal Normalizing Flows	May 6, 2024	Causal Inferencecounterfactual	—Unverified	0
Deep Learning for Causal Inference: A Comparison of Architectures for Heterogeneous Treatment Effect Estimation	May 6, 2024	Causal InferenceHeterogeneous Treatment Effect Estimation	—Unverified	0
A causal inference approach of monosynapses from spike trains	May 5, 2024	Causal InferenceFunctional Connectivity	—Unverified	0
On Probabilistic and Causal Reasoning with Summation Operators	May 5, 2024	Causal Inference	—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