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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 661–670 of 1722 papers

Title	Date	Tasks	Status	Hype
A Brief Review of Hypernetworks in Deep Learning	Jun 12, 2023	Causal InferenceContinual Learning	CodeCode Available	0
Leveraging text data for causal inference using electronic health records	Jun 9, 2023	Causal InferenceImputation	CodeCode Available	0
Can Large Language Models Infer Causation from Correlation?	Jun 9, 2023	Causal Inference	CodeCode Available	1
Task-specific experimental design for treatment effect estimation	Jun 8, 2023	Causal InferenceExperimental Design	—Unverified	0
A Causal Framework for Decomposing Spurious Variations	Jun 8, 2023	Causal InferenceEpidemiology	—Unverified	0
Timing Process Interventions with Causal Inference and Reinforcement Learning	Jun 7, 2023	Causal Inferencereinforcement-learning	—Unverified	0
Finding Counterfactually Optimal Action Sequences in Continuous State Spaces	Jun 6, 2023	Causal InferenceDecision Making	CodeCode Available	0
Intervention Generalization: A View from Factor Graph Models	Jun 6, 2023	Causal InferenceExperimental Design	—Unverified	0
Contagion Effect Estimation Using Proximal Embeddings	Jun 4, 2023	Causal InferenceRepresentation Learning	—Unverified	0
Individual Causal Inference Using Panel Data With Multiple Outcomes	Jun 3, 2023	Causal 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