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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 1001–1010 of 1722 papers

Title	Date	Tasks	Status	Hype
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning	Feb 17, 2022	Causal Inferencecounterfactual	CodeCode Available	1
Long-term Causal Inference Under Persistent Confounding via Data Combination	Feb 15, 2022	Causal Inference	CodeCode Available	0
Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplace	Feb 10, 2022	Causal Inferencereinforcement-learning	—Unverified	0
Benign-Overfitting in Conditional Average Treatment Effect Prediction with Linear Regression	Feb 10, 2022	Causal Inferenceregression	—Unverified	0
Validating Causal Inference Methods	Feb 9, 2022	Causal Inferencecounterfactual	—Unverified	0
HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary fashion time series	Feb 7, 2022	Causal InferenceTime Series	CodeCode Available	0
Targeted-BEHRT: Deep learning for observational causal inference on longitudinal electronic health records	Feb 7, 2022	Causal InferenceDecision Making	CodeCode Available	1
Evaluation Methods and Measures for Causal Learning Algorithms	Feb 7, 2022	BenchmarkingBIG-bench Machine Learning	—Unverified	0
Causal Inference Using Tractable Circuits	Feb 7, 2022	Causal Inference	—Unverified	0
Deep End-to-end Causal Inference	Feb 4, 2022	Causal DiscoveryCausal 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