A new test statistic and bootstrap for independence testing of high-dimensional nonstationary time series that avoids whitening by removing temporal dependence bias under the null.
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A weighted K-means plus decision-tree pipeline learns multi-action policies from observational data and is applied to HCV treatment choices for HIV co-infected patients, finding a high-clearance subgroup and potential cost savings of CAN$3.6-4.9 million.
A fused CNN-ViT model achieves 97.32% accuracy distinguishing AI-generated from real images on the CIFAKE dataset.
Compares bridge equation and array decomposition proxy methods for causal identification, highlighting differences in model restrictions and scope of applicability.
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Tests for Independence of High-Dimensional Nonstationary Time Series
A new test statistic and bootstrap for independence testing of high-dimensional nonstationary time series that avoids whitening by removing temporal dependence bias under the null.
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Policy Learning with Observational Data: The Case of Hepatitis C Treatment for HIV/HCV Co-Infected Patients
A weighted K-means plus decision-tree pipeline learns multi-action policies from observational data and is applied to HCV treatment choices for HIV co-infected patients, finding a high-clearance subgroup and potential cost savings of CAN$3.6-4.9 million.
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AI-Generated Image Recognition via Fusion of CNNs and Vision Transformers
A fused CNN-ViT model achieves 97.32% accuracy distinguishing AI-generated from real images on the CIFAKE dataset.
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Comparing Two Proxy Methods for Causal Identification
Compares bridge equation and array decomposition proxy methods for causal identification, highlighting differences in model restrictions and scope of applicability.