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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 381–390 of 1722 papers

Title	Date	Tasks	Status	Hype
Adaptive Nonparametric Perturbations of Parametric Bayesian Models	Dec 14, 2024	Bayesian InferenceCausal Inference	CodeCode Available	0
Do LLMs Act as Repositories of Causal Knowledge?	Dec 14, 2024	Causal InferenceMultiple-choice	—Unverified	0
Learning Structural Causal Models from Ordering: Identifiable Flow Models	Dec 13, 2024	Causal Inferencecounterfactual	—Unverified	0
Multimodal Sentiment Analysis Based on Causal Reasoning	Dec 10, 2024	Causal Inferencecounterfactual	—Unverified	0
Political-LLM: Large Language Models in Political Science	Dec 9, 2024	Causal Inferencecounterfactual	—Unverified	0
A Compositional Atlas for Algebraic Circuits	Dec 7, 2024	Causal Inference	—Unverified	0
Estimating the treatment effect over time under general interference through deep learner integrated TMLE	Dec 6, 2024	Causal Inferencecounterfactual	—Unverified	0
Deep Causal Inference for Point-referenced Spatial Data with Continuous Treatments	Dec 5, 2024	Causal InferenceDecision Making	CodeCode Available	0
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data	Dec 5, 2024	Causal Inferencecounterfactual	—Unverified	0
Disentangled Representation Learning for Causal Inference with Instruments	Dec 5, 2024	Causal InferenceRepresentation Learning	—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