Scientific Research Publishing

Kipf, T. and Welling, M. (2016) Semi-Supervised Classification with Graph Convolutional Networks. arXiv: 1609.02907.

ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
Frontiers

BioMedKG: multimodal contrastive representation learning in augmented BioMedical knowledge graphs

1 Department of Computer Science, The University of Alabama at Birmingham, Birmingham, AL, United States 2 Department of Computer Science, Washington University in St. Louis, St. Louis, MO, United ...
IEEE

Graph Representation Learning Combining Denoising and Masked Reconstruction With Contrastive Learning

Abstract: In the field of graph self-supervised learning (GSSL), graph autoencoders and graph contrastive learning are two mainstream methods. Graph autoencoders aim to learn representations by ...
Frontiers

Multi-Scale graph wavelet convolutional network for hyperspectral image classification

Hyperspectral images (HSIs) have very high dimensionality and typically lack sufficient labeled samples, which significantly challenges their processing and analysis. These challenges contribute to ...
C&EN

Integrating ESM-2 and Graph Neural Networks with AlphaFold-2 Structures for Enhanced Protein Function Prediction

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
Scientific Research Publishing

An In-Depth Analysis of Graph Neural Networks and Machine Learning Approaches for Drug Repositioning ()

1 Department of Computer Science and Engineering, Kishoreganj University, Kishoreganj, Bangladesh. 2 Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh. 3 ...