MLB pitchers have a ridiculous number of tools at their disposal. They throw triple-digit fastballs, rip high-spin breaking balls, and show off pinpoint command. Although these are the most visible – ...

Machine learning has expanded beyond traditional Euclidean spaces in recent years, exploring representations in more complex geometric structures. Non-Euclidean representation learning is a growing ...

Abstract: Euclidean distance transforms are fundamental in image processing and computer vision, with critical applications in medical image analysis and computer graphics. However, existing ...

ABSTRACT: Purpose: This study describes a machine-learning approach utilizing patients' anatomical changes to predict parotid mean dose changes in fractionated radiotherapy for head-and-neck cancer, ...

This Paper addresses the limitations of classical machine learning approaches primarily developed for data lying in Euclidean space. Modern machine learning increasingly encounters richly structured ...

I attempted to calculate the Euclidean distance matrix between the regional centers of mass using the provided sc and fc matrices. However, the result does not match the Euclidean distance matrix ...