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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 381–390 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Counterfactual Fairness	Mar 20, 2017	BIG-bench Machine LearningCausal Inference	CodeCode Available	0	5
Extrapolating Treatment Effects in Multi-Cutoff Regression Discontinuity Designs	Aug 13, 2018	Causal Inferenceregression	CodeCode Available	0	5
Counterfactual Prediction Under Selective Confounding	Oct 21, 2023	AllCausal Inference	CodeCode Available	0	5
Covariate balancing using the integral probability metric for causal inference	May 23, 2023	Causal Inferenceregression	CodeCode Available	0	5
On the power of conditional independence testing under model-X	May 12, 2020	Causal InferenceLEMMA	CodeCode Available	0	5
APEX: Empowering LLMs with Physics-Based Task Planning for Real-time Insight	May 20, 2025	Causal InferenceDecision Making	CodeCode Available	0	5
CORECODE: A Common Sense Annotated Dialogue Dataset with Benchmark Tasks for Chinese Large Language Models	Dec 20, 2023	Causal InferenceCommon Sense Reasoning	CodeCode Available	0	5
Convolutional neural networks for valid and efficient causal inference	Jan 27, 2023	Causal Inferencevalid	CodeCode Available	0	5
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial Nets	Jan 1, 2018	Causal Inferencecounterfactual	CodeCode Available	0	5
Counterfactual and Synthetic Control Method: Causal Inference with Instrumented Principal Component Analysis	Aug 17, 2024	Causal Inferencecounterfactual	CodeCode Available	0	5

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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