IEEE

A Graph Representation Learning Approach for Imbalanced Ship Type Recognition Using AIS Trajectory Data

Abstract: Marine transportation constitutes a vital segment of international trade logistics. Recognizing marine carrier ship types is essential for the governance and efficiency of the marine ...
C&EN

KGG: Knowledge-Guided Graph Self-Supervised Learning to Enhance Molecular Property Predictions

Faculty of Pharmacy, University of Medicine and Pharmacy at Ho Chi Minh City, 41 Dinh Tien Hoang, District 1, Ho Chi Minh City 700000, Vietnam ...
The Washington Post

The health risks from plastics almost nobody knows about

Phthalates, chemicals found in plastics, are linked to an array of problems, especially in pregnancy Warning: This graphic requires JavaScript. Please enable ...
Frontiers

Learning Gaussian graphical models from correlated data

Gaussian Graphical Models (GGMs) are a type of network modeling that uses partial correlation rather than correlation for representing complex relationships among multiple variables. The advantage of ...
IEEE

An Adaptive Multi-Granularity Graph Representation of Image via Granular-ball Computing

Abstract: Graph neural networks (GNNs) encounter challenges in establishing deep structures and managing a large number of parameters effectively to learn node features comprehensively. Consequently, ...
C&EN

Accurate Predictions of Molecular Properties of Proteins via Graph Neural Networks and Transfer Learning

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