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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 171–180 of 1722 papers

Title	Date	Tasks	Status	Hype
Disentangling User Interest and Conformity for Recommendation with Causal Embedding	Jun 19, 2020	Causal Inference	CodeCode Available	1
Learning Invariant Representations for Reinforcement Learning without Reconstruction	Jun 18, 2020	Causal InferenceMuJoCo	CodeCode Available	1
Causal intersectionality for fair ranking	Jun 15, 2020	Causal InferenceFairness	CodeCode Available	1
Learning Individually Inferred Communication for Multi-Agent Cooperation	Jun 11, 2020	Causal InferenceMulti-agent Reinforcement Learning	CodeCode Available	1
Counterfactual VQA: A Cause-Effect Look at Language Bias	Jun 8, 2020	Causal Inferencecounterfactual	CodeCode Available	1
Automatic Detection of Influential Actors in Disinformation Networks	May 21, 2020	Causal Inference	CodeCode Available	1
Causal Modeling of Twitter Activity During COVID-19	May 16, 2020	Causal InferenceDescriptive	CodeCode Available	1
Multivariate Time Series Forecasting with Transfer Entropy Graph	May 3, 2020	Causal InferenceDecision Making	CodeCode Available	1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric Approaches	Apr 15, 2020	Bayesian InferenceCausal Inference	CodeCode Available	1
Invariant Causal Prediction for Block MDPs	Mar 12, 2020	Causal InferencePrediction	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