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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 141–150 of 1722 papers

Title	Date	Tasks	Status	Hype
Causal Reinforcement Learning using Observational and Interventional Data	Jun 28, 2021	Causal InferenceModel-based Reinforcement Learning	CodeCode Available	1
CausalNLP: A Practical Toolkit for Causal Inference with Text	Jun 15, 2021	Causal Inference	CodeCode Available	1
Variational Causal Networks: Approximate Bayesian Inference over Causal Structures	Jun 14, 2021	Bayesian InferenceCausal Inference	CodeCode Available	1
Learning from Counterfactual Links for Link Prediction	Jun 3, 2021	Causal Inferencecounterfactual	CodeCode Available	1
Federated Estimation of Causal Effects from Observational Data	May 31, 2021	Causal InferenceGaussian Processes	CodeCode Available	1
An Influence-based Approach for Root Cause Alarm Discovery in Telecom Networks	May 7, 2021	Causal InferenceFault localization	CodeCode Available	1
Everything Has a Cause: Leveraging Causal Inference in Legal Text Analysis	Apr 19, 2021	Causal Inference	CodeCode Available	1
SUTD-TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic Events	Mar 29, 2021	Autonomous VehiclesBenchmarking	CodeCode Available	1
SEMgraph: An R Package for Causal Network Analysis of High-Throughput Data with Structural Equation Models	Mar 15, 2021	Causal Inference	CodeCode Available	1
A Structural Causal Model for MR Images of Multiple Sclerosis	Mar 4, 2021	Causal Inferencecounterfactual	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