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 ...

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 ...

Node classification, as a central task in the graph data analysis, has been studied extensively with network embedding technique for single-layer graph network. However, there are some obstacles when ...

Citation: Nunez-Iglesias J, Kennedy R, Plaza SM, Chakraborty A and Katz WT (2014) Graph-based active learning of agglomeration (GALA): a Python library to segment 2D and 3D neuroimages. Front.

Convolutional neural networks have achieved great advantages in the hyperspectral image (HSI) classification. Nevertheless, their ability to model topological relations among samples is limited, ...