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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 731–740 of 1722 papers

Title	Date	Tasks	Status	Hype
Bayesian Causal Forests for Multivariate Outcomes: Application to Irish Data From an International Large Scale Education Assessment	Mar 8, 2023	Causal Inferenceregression	—Unverified	0
Inference on Optimal Dynamic Policies via Softmax Approximation	Mar 8, 2023	Causal InferenceDecision Making	CodeCode Available	0
Learning When to Treat Business Processes: Prescriptive Process Monitoring with Causal Inference and Reinforcement Learning	Mar 7, 2023	Causal InferenceConformal Prediction	CodeCode Available	0
Environment Invariant Linear Least Squares	Mar 6, 2023	Causal Inferenceregression	CodeCode Available	0
Estimating Treatment Effects from Irregular Time Series Observations with Hidden Confounders	Mar 4, 2023	Causal InferenceIrregular Time Series	—Unverified	0
Continual Causal Inference with Incremental Observational Data	Mar 3, 2023	Causal Inferencecounterfactual	—Unverified	0
PAGE: A Position-Aware Graph-Based Model for Emotion Cause Entailment in Conversation	Mar 3, 2023	Causal Emotion EntailmentCausal Inference	CodeCode Available	1
Hyperparameter Tuning and Model Evaluation in Causal Effect Estimation	Mar 2, 2023	Causal InferenceModel Selection	CodeCode Available	0
Learning high-dimensional causal effect	Mar 1, 2023	Causal InferenceVocal Bursts Intensity Prediction	CodeCode Available	0
Representation Disentaglement via Regularization by Causal Identification	Feb 28, 2023	Causal IdentificationCausal 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