This research provides density functions and descriptive statistics for the distance between points for basic shapes in Cartesian space. Both Euclidean and Rectilinear Distances are determined for ...
1 Laboratory of Bioinformatics and Systems, Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, Brazil 2 Laboratory of Bioinformatics, Visualization and Systems, ...
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 ...
Background: In-feed antibiotic growth promoters (AGPs) have been a cornerstone in the livestock industry due to their role in enhancing growth and feed efficiency. However, concerns over antibiotic ...
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, ...
Abstract: For a point set, Euclidean distance matrix (EDM) is the matrix consisting of squared distances between every pair of points in the set. It frequently appears in wide ranging applications ...
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