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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 1401–1410 of 1722 papers

Title	Date	Tasks	Status	Hype
Does Terrorism Trigger Online Hate Speech? On the Association of Events and Time Series	Apr 30, 2020	Causal InferencePoint Processes	CodeCode Available	0
MultiMBNN: Matched and Balanced Causal Inference with Neural Networks	Apr 28, 2020	Causal Inference	—Unverified	0
Causal Modeling with Stochastic Confounders	Apr 24, 2020	Causal Inference	—Unverified	0
Machine learning for causal inference: on the use of cross-fit estimators	Apr 21, 2020	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
Learning Continuous Treatment Policy and Bipartite Embeddings for Matching with Heterogeneous Causal Effects	Apr 21, 2020	Causal Inferencecounterfactual	—Unverified	0
Causal Inference under Outcome-Based Sampling with Monotonicity Assumptions	Apr 17, 2020	Causal Inference	CodeCode Available	0
Ivy: Instrumental Variable Synthesis for Causal Inference	Apr 11, 2020	Causal InferenceEpidemiology	—Unverified	0
A category theoretical argument for causal inference	Apr 9, 2020	Causal Inference	—Unverified	0
Causal Relational Learning	Apr 7, 2020	Causal InferenceDecision Making	—Unverified	0
Identification Methods With Arbitrary Interventional Distributions as Inputs	Apr 2, 2020	Causal Inferencecounterfactual	—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