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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 201–210 of 1722 papers

Title	Date	Tasks	Status	Hype
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
Disentangled Representation Learning for Causal Inference with Instruments	Dec 5, 2024	Causal InferenceRepresentation Learning	—Unverified	0
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data	Dec 5, 2024	Causal Inferencecounterfactual	—Unverified	0
Online Experimental Design With Estimation-Regret Trade-off Under Network Interference	Dec 4, 2024	Causal InferenceExperimental Design	—Unverified	0
Nature versus nurture in galaxy formation: the effect of environment on star formation with causal machine learning	Dec 3, 2024	AstronomyCausal 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