From each candidate point, a local fragment of 35 × 35 pixels is extracted and used as input to the classification model. A Convolutional Neural Network (CNN) model, tailored for small image datasets ...

Molecular representation learning has attracted much attention recently. A molecule can be viewed as a 2D graph with nodes/atoms connected by edges/bonds, and can also be represented by a 3D ...

Most of the recent research in data visualization has focused on technical and aesthetic issues involved in the manipulation of graphs, specifically on features that facilitate data exploration to ...

Research team led by Chuliang Weng introduces D2-GCN, a groundbreaking disentangled graph convolutional network that dynamically adjusts feature channels for enhanced node representation ...

Illustration of the comparative analysis between graph filtration and Vietoris-Rips filtration for both dimension-0 (H0) and dimension-1 (H1) in the classification of (A) healthy controls (HC) vs.

From each candidate point, a local fragment of 35×35 pixels is extracted and used as input to the classification model. A Convolutional Neural Network (CNN) model, tailored for small image datasets ...