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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 191–200 of 1722 papers

Title	Date	Tasks	Status	Hype
From Correlation to Causation: Understanding Climate Change through Causal Analysis and LLM Interpretations	Dec 21, 2024	Causal InferenceDecision Making	—Unverified	0
A Systems Thinking Approach to Algorithmic Fairness	Dec 21, 2024	Causal InferenceFairness	—Unverified	0
Eliciting Causal Abilities in Large Language Models for Reasoning Tasks	Dec 19, 2024	Causal Inference	CodeCode Available	1
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal Discovery	Dec 18, 2024	Causal DiscoveryCausal Inference	CodeCode Available	1
Causally Consistent Normalizing Flow	Dec 16, 2024	Causal Inference	—Unverified	0
On the Role of Surrogates in Conformal Inference of Individual Causal Effects	Dec 16, 2024	Causal InferenceConformal Prediction	CodeCode Available	0
Moderating the Mediation Bootstrap for Causal Inference	Dec 15, 2024	Causal Inference	—Unverified	0
ABC3: Active Bayesian Causal Inference with Cohn Criteria in Randomized Experiments	Dec 15, 2024	Active LearningCausal Inference	CodeCode Available	0
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

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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