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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 11–20 of 1722 papers

Title	Date	Tasks	Status	Hype
Causal Evaluation of Language Models	May 1, 2024	Causal DiscoveryCausal Inference	CodeCode Available	2
Vision-and-Language Navigation via Causal Learning	Apr 16, 2024	Causal InferenceContrastive Learning	CodeCode Available	2
Hierarchical NeuroSymbolic Approach for Comprehensive and Explainable Action Quality Assessment	Mar 20, 2024	Action Quality AssessmentAction Quality Assessment Report Generation	CodeCode Available	2
Applied Causal Inference Powered by ML and AI	Mar 4, 2024	Causal Inference	CodeCode Available	2
Salesforce CausalAI Library: A Fast and Scalable Framework for Causal Analysis of Time Series and Tabular Data	Jan 25, 2023	Causal DiscoveryCausal Inference	CodeCode Available	2
Out-of-sample scoring and automatic selection of causal estimators	Dec 20, 2022	Causal InferenceHyperparameter Optimization	CodeCode Available	2
Deep Reinforcement Learning for Multi-Agent Interaction	Aug 2, 2022	BIG-bench Machine LearningCausal Inference	CodeCode Available	2
Unifying Pairwise Interactions in Complex Dynamics	Jan 28, 2022	Causal InferenceTime Series	CodeCode Available	2
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End	Nov 10, 2020	Causal Inferencecounterfactual	CodeCode Available	2
Unbiased Scene Graph Generation from Biased Training	Feb 27, 2020	Causal Inferencecounterfactual	CodeCode Available	2

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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