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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 1481–1490 of 1722 papers

Title	Date	Tasks	Status	Hype
Identification In Missing Data Models Represented By Directed Acyclic Graphs	Jun 29, 2019	Causal Inference	—Unverified	0
Causal Inference Under Interference And Network Uncertainty	Jun 29, 2019	Causal Inference	—Unverified	0
Learning Causal State Representations of Partially Observable Environments	Jun 25, 2019	Causal InferenceReinforcement Learning	—Unverified	0
A Bayesian Solution to the M-Bias Problem	Jun 17, 2019	Causal Inference	—Unverified	0
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation	Jun 12, 2019	Causal InferenceDecision Making	CodeCode Available	0
Learning Individual Causal Effects from Networked Observational Data	Jun 8, 2019	Causal Inference	CodeCode Available	0
Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck	Jun 7, 2019	Causal Inference	—Unverified	0
Gradient-Based Neural DAG Learning	Jun 5, 2019	Causal Inference	CodeCode Available	0
Adapting Neural Networks for the Estimation of Treatment Effects	Jun 5, 2019	Causal Inference	CodeCode Available	0
The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis	Jun 4, 2019	BIG-bench Machine LearningCausal 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