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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 461–470 of 1722 papers

Title	Date	Tasks	Status	Hype
Unveiling the Potential of Robustness in Selecting Conditional Average Treatment Effect Estimators	Feb 28, 2024	Causal Inferencecounterfactual	CodeCode Available	0
Treatment effects without multicollinearity? Temporal order and the Gram-Schmidt process in causal inference	Feb 27, 2024	Causal InferenceReading Comprehension	CodeCode Available	0
Towards Generalizing Inferences from Trials to Target Populations	Feb 26, 2024	Causal Inferencevalid	—Unverified	0
Impact of Physical Activity on Quality of Life During Pregnancy: A Causal ML Approach	Feb 25, 2024	Causal DiscoveryCausal Inference	—Unverified	0
ROS-Causal: A ROS-based Causal Analysis Framework for Human-Robot Interaction Applications	Feb 25, 2024	Causal DiscoveryCausal Inference	CodeCode Available	0
Statistical Agnostic Regression: a machine learning method to validate regression models	Feb 23, 2024	Causal InferenceData Integration	—Unverified	0
Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models	Feb 23, 2024	Causal InferenceRetrieval	—Unverified	0
Optimizing Language Models for Human Preferences is a Causal Inference Problem	Feb 22, 2024	Causal InferenceLanguage Modeling	—Unverified	0
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders	Feb 22, 2024	Causal InferenceGaussian Processes	CodeCode Available	0
Structure-agnostic Optimality of Doubly Robust Learning for Treatment Effect Estimation	Feb 22, 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