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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 831–840 of 1722 papers

Title	Date	Tasks	Status	Hype
Spectral Representation Learning for Conditional Moment Models	Oct 29, 2022	Causal InferenceRepresentation Learning	—Unverified	0
Causal DAG extraction from a library of books or videos/movies	Oct 29, 2022	Causal Inference	—Unverified	0
A Survey on Causal Representation Learning and Future Work for Medical Image Analysis	Oct 28, 2022	Causal InferenceMedical Image Analysis	CodeCode Available	0
Sample-Specific Root Causal Inference with Latent Variables	Oct 27, 2022	Causal Inference	—Unverified	0
Dynamic Survival Transformers for Causal Inference with Electronic Health Records	Oct 25, 2022	Causal InferenceSurvival Analysis	—Unverified	0
Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network	Oct 25, 2022	Adversarial RobustnessCausal Inference	—Unverified	0
LMPriors: Pre-Trained Language Models as Task-Specific Priors	Oct 22, 2022	Causal InferenceCommon Sense Reasoning	—Unverified	0
Causally-guided Regularization of Graph Attention Improves Generalizability	Oct 20, 2022	Causal InferenceGraph Attention	—Unverified	0
Granger causal inference on DAGs identifies genomic loci regulating transcription	Oct 18, 2022	Causal Inference	CodeCode Available	1
Vision Paper: Causal Inference for Interpretable and Robust Machine Learning in Mobility Analysis	Oct 18, 2022	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