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Analysis of Variance of Tensor Product Reproducing Kernel Hilbert Spaces on Metric Spaces
Many methods have been developed to analyze complex data, such as non-Euclidean shape, network, and manifold data. However, there is a …
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COVINet: A deep learning-based and interpretable prediction model for the county-wise trajectories of COVID-19 in the United States
The devastating impact of COVID-19 on the United States has been profound since its onset in January 2020. Predicting the trajectory of …
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skscope: Fast Sparsity-Constrained Optimization in Python
Applying iterative solvers on sparsity-constrained optimization (SCO) requires tedious mathematical deduction and careful …
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An improved strategy for predicting alzheimer’s disease progression in patients with mild cognitive impairment by clustering hippocampal shape data
Alzheimer’s disease (AD), a neurodegenerative disorder leading to dementia and cognitive deficits, is influenced by various risk …
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Towards better clinical prediction and interpretation via a new imputation strategy from National Health and Nutrition Examination Survey
Heart failure (HF) is a long-term condition that worsens over time, which means the heart is not able to pump blood as well as it …
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Green's matching: an efficient approach to parameter estimation in complex dynamic systems
Parameters of differential equations are essential to characterize intrinsic behaviours of dynamic systems. Numerous methods for …
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Enhancing Retinal Fundus Image Quality Assessment With Swin-Transformer--Based Learning Across Multiple Color-Spaces
Purpose:The assessment of retinal image (RI) quality holds significant importance in both clinical trials and large datasets, because …
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Variable selection in additive models via hierarchical sparse penalty
As a popular tool for nonlinear models, additive models work efficiently with nonparametric estimation. However, naively applying the …
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Copy number variation detection based on constraint least squares
Copy number variations (CNVs) are a form of structural variation of a DNA sequence, including amplification and deletion of a …
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Nonparametric two-sample tests of high dimensional mean vectors via random integration
Testing the equality of the means in two samples is a fundamental statistical inferential problem. Most of the existing methods are …
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