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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 211–220 of 1722 papers

Title	Date	Tasks	Status	Hype
CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public Events	Dec 3, 2024	ArticlesCausal Inference	CodeCode Available	1
Practical Performative Policy Learning with Strategic Agents	Dec 2, 2024	Causal Inference	CodeCode Available	0
A Comprehensive Guide to Explainable AI: From Classical Models to LLMs	Dec 1, 2024	Causal Inferencecounterfactual	CodeCode Available	2
COLD: Causal reasOning in cLosed Daily activities	Nov 29, 2024	Causal InferenceCommonsense Causal Reasoning	CodeCode Available	0
Causal Inference in Finance: An Expertise-Driven Model for Instrument Variables Identification and Interpretation	Nov 26, 2024	Causal Inferencecounterfactual	—Unverified	0
OccludeNet: A Causal Journey into Mixed-View Actor-Centric Video Action Recognition under Occlusions	Nov 24, 2024	Action ClassificationAction Recognition	CodeCode Available	0
Double Machine Learning for Adaptive Causal Representation in High-Dimensional Data	Nov 22, 2024	Causal InferenceComputational Efficiency	—Unverified	0
Logarithmic Neyman Regret for Adaptive Estimation of the Average Treatment Effect	Nov 21, 2024	Causal InferenceOff-policy evaluation	—Unverified	0
Generative Intervention Models for Causal Perturbation Modeling	Nov 21, 2024	Causal Inference	—Unverified	0
Heterophilic Graph Neural Networks Optimization with Causal Message-passing	Nov 21, 2024	Causal InferenceGraph 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