Data is the driving force of machine learning, with the amount and quality of training data
often being more important for the performance of a system than architecture and training …

Knee osteoarthritis (KOA) is a degenerative joint disease, which significantly affects middle-
aged and elderly people. The majority of KOA is primarily based on hyaline cartilage …

This article studies self-supervised graph representation learning, which is critical to various
tasks, such as protein property prediction. Existing methods typically aggregate …

This article elaborates on intellectual monopoly theory as a form of predation and rentiership
using Amazon as a case study. By analysing Amazon's financial statements, scientific …

Unsupervised domain adaptation (UDA) carries out knowledge transfer from the labeled
source domain to the unlabeled target domain. Existing feature alignment methods in UDA …

In 1961, Gomory and Hu showed that the All-Pairs Max-Flow problem of computing the max-
flow between all n\2 pairs of vertices in an undirected graph can be solved using only n-1 …

Background Automatic segmentation of 3D objects in computed tomography (CT) is
challenging. Current methods, based mainly on artificial intelligence (AI) and end‐to‐end …

In image segmentation, for the condition that objects (targets) and background in an image
are intertwined or their common boundaries are vague as well as their textures are similar …

We propose topology-aware feature partitioning into $ k $ disjoint partitions for given scene
features as a method for object-centric representation learning. To this end, we propose to …

Graph node clustering methods, which aim to partition graph vertices into several disjoint
groups of data with similar features, are usually fulfilled based on topological structural …