Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
A signal-processing–based framework converts DNA sequences into numerical signals to identify protein-coding regions. By integrating spectral analysis and SVM classification, the approach improves ...
Abstract: Owing to pronounced inter-individual variability in biological signals, transfer learning has emerged as a widely used strategy to reduce calibration requirements for new users. Among the ...
Mouse primary motor and somatosensory cortices contain detailed information about the many time-varying arm and paw joint ...
Abstract: Identity matching (ID matching) across domains using skull or facial features is a challenging task, particularly when transitioning from homogeneous-domain (face-face) to ...
The application of several high-throughput genomic and proteomic technologies to address questions in cancer diagnosis, prognosis and prediction generate high-dimensional data sets. The multimodality ...
The problem consists in classifying molecular graphs into two categories, depending on whether or not they exhibit a specific function. To tackle this, we aim to explore graph kernels for generating ...
Code repository for experiments and figures in the main text of the paper "Uncertainty Quantification with the Empirical Neural Tangent Kernel". The NUQLS method has been released as a package.
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