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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 1361–1370 of 1722 papers

Title	Date	Tasks	Status	Hype
DAG-aware Transformer for Causal Effect Estimation	Oct 13, 2024	Causal Inference	CodeCode Available	0
Counterfactual and Synthetic Control Method: Causal Inference with Instrumented Principal Component Analysis	Aug 17, 2024	Causal Inferencecounterfactual	CodeCode Available	0
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
Robustness Against Weak or Invalid Instruments: Exploring Nonlinear Treatment Models with Machine Learning	Mar 24, 2022	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach	Feb 2, 2024	Causal DiscoveryCausal Inference	CodeCode Available	0
uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative Filtering	May 22, 2023	Causal InferenceCollaborative Filtering	CodeCode Available	0
A Commonsense Reasoning Framework for Explanatory Emotion Attribution, Generation and Re-classification	Jan 11, 2021	Causal Emotion EntailmentCausal Inference	CodeCode Available	0
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal Inference	CodeCode Available	0
Subset verification and search algorithms for causal DAGs	Jan 9, 2023	Causal Inference	CodeCode Available	0
CausalMed: Causality-Based Personalized Medication Recommendation Centered on Patient health state	Apr 18, 2024	Causal DiscoveryCausal Inference	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