SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 326–350 of 1722 papers

TitleStatusHype
A Forecaster's Review of Judea Pearl's Causality: Models, Reasoning and Inference, Second Edition, 2009—0
A step towards the applicability of algorithms based on invariant causal learning on observational data—0
Assimilative Causal Inference—0
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem—0
Causal Inference of Script Knowledge—0
SBI: A Simulation-Based Test of Identifiability for Bayesian Causal Inference—0
Nested Nonparametric Instrumental Variable Regression—0
Causal inference in network experiments: regression-based analysis and design-based properties—0
Affirmative Algorithms: The Legal Grounds for Fairness as Awareness—0
A Semiparametric Approach to Causal Inference—0
Achieving Counterfactual Fairness for Causal Bandit—0
Causal Inference in Non-linear Time-series using Deep Networks and Knockoff Counterfactuals—0
Causal Graph Aided Causal Discovery in an Observational Aneurysmal Subarachnoid Hemorrhage Study—0
Causal GNNs: A GNN-Driven Instrumental Variable Approach for Causal Inference in Networks—0
Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward—0
Causal Forecasting for Pricing—0
Causal Post-Processing of Predictive Models—0
Artificial Intelligence for Personalized Prediction of Alzheimer's Disease Progression: A Survey of Methods, Data Challenges, and Future Directions—0
Causal Graph Discovery with Retrieval-Augmented Generation based Large Language Models—0
Causal Identification with Additive Noise Models: Quantifying the Effect of Noise—0
Identifying causal effects with subjective ordinal outcomes—0
A fast PC algorithm for high dimensional causal discovery with multi-core PCs—0
Causal Feature Selection with Dimension Reduction for Interpretable Text Classification—0
Artificial Intelligence and Aesthetic Judgment—0
Causal Inference in Geosciences with Kernel Sensitivity Maps—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Random ForestAverage Treatment Effect Error0.96—Unverified
2Balancing Linear RegressionAverage Treatment Effect Error0.93—Unverified
3k-NNAverage Treatment Effect Error0.79—Unverified
4CEVAEAverage Treatment Effect Error0.46—Unverified
5Balancing Neural NetworkAverage Treatment Effect Error0.42—Unverified
6Causal ForestAverage Treatment Effect Error0.4—Unverified
7BCAUS DRAverage Treatment Effect Error0.29—Unverified
8TARNetAverage Treatment Effect Error0.28—Unverified
9Counterfactual Regression + WASSAverage Treatment Effect Error0.27—Unverified
10MTDL-KNNAverage Treatment Effect Error0.23—Unverified
#ModelMetricClaimedVerifiedStatus
1CFR WASSAverage Treatment Effect on the Treated Error0.09—Unverified
2CFR MMDAverage Treatment Effect on the Treated Error0.08—Unverified
3BARTAverage Treatment Effect on the Treated Error0.08—Unverified
4GANITEAverage Treatment Effect on the Treated Error0.06—Unverified
5BCAUSSAverage Treatment Effect on the Treated Error0.05—Unverified
#ModelMetricClaimedVerifiedStatus
1BARTAverage Treatment Effect Error0.34—Unverified
2OLS with separate regressors for each treatmentAverage Treatment Effect Error0.31—Unverified
3Average Treatment Effect Error-0.23—Unverified