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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 1491–1500 of 1722 papers

Title	Date	Tasks	Status	Hype
Robustifying Independent Component Analysis by Adjusting for Group-Wise Stationary Noise	Jun 4, 2018	Causal InferenceEEG	CodeCode Available	0
Whittemore: An embedded domain specific language for causal programming	Dec 21, 2018	Causal Inference	CodeCode Available	0
Causal Estimation of Exposure Shifts with Neural Networks	Feb 6, 2023	Causal Inference	CodeCode Available	0
Learning high-dimensional causal effect	Mar 1, 2023	Causal InferenceVocal Bursts Intensity Prediction	CodeCode Available	0
Toward Informed AV Decision-Making: Computational Model of Well-being and Trust in Mobility	May 21, 2025	Causal InferenceDecision Making	CodeCode Available	0
Can Transformers Do Enumerative Geometry?	Aug 27, 2024	Activation Function SynthesisCausal Inference	CodeCode Available	0
Learning Individual Causal Effects from Networked Observational Data	Jun 8, 2019	Causal Inference	CodeCode Available	0
Orthogonal Machine Learning: Power and Limitations	Nov 1, 2017	2kBIG-bench Machine Learning	CodeCode Available	0
ROS-Causal: A ROS-based Causal Analysis Framework for Human-Robot Interaction Applications	Feb 25, 2024	Causal DiscoveryCausal Inference	CodeCode Available	0
Enhancing Model Robustness and Fairness with Causality: A Regularization Approach	Oct 3, 2021	Causal Inferencecounterfactual	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