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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 131–140 of 1722 papers

Title	Date	Tasks	Status	Hype
Optimization-based Causal Estimation from Heterogenous Environments	Sep 24, 2021	Causal Inference	CodeCode Available	1
Uncovering Main Causalities for Long-tailed Information Extraction	Sep 11, 2021	Causal Inferencecounterfactual	CodeCode Available	1
Counterfactual Explainable Recommendation	Aug 24, 2021	Causal Inferencecounterfactual	CodeCode Available	1
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification	Aug 19, 2021	Causal Inferencecounterfactual	CodeCode Available	1
Causal Incremental Graph Convolution for Recommender System Retraining	Aug 16, 2021	Causal InferenceRecommendation Systems	CodeCode Available	1
Towards Unbiased Visual Emotion Recognition via Causal Intervention	Jul 26, 2021	Causal InferenceEmotion Recognition	CodeCode Available	1
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition	Jul 13, 2021	Causal Inferencecounterfactual	CodeCode Available	1
Algorithmic Causal Effect Identification with causaleffect	Jul 9, 2021	Causal Inference	CodeCode Available	1
Spatiotemporal information conversion machine for time-series prediction	Jul 3, 2021	Causal InferencePrediction	CodeCode Available	1
The Causal-Neural Connection: Expressiveness, Learnability, and Inference	Jul 2, 2021	Causal IdentificationCausal Inference	CodeCode Available	1

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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