and modern deep learning. They explored flexible learning-based approaches which implement strong relational inductive biases to capitalize on explicitly structured representations and computations, ...

Also: Google Brain, Microsoft plumb the mysteries of networks with AI The paper, "Relational inductive biases, deep learning, and graph networks," posted on the arXiv pre-print service ...

A research team from Kumamoto University has developed a promising deep learning model that significantly ... However, conventional Graph Neural Networks (GNNs) often struggle with accuracy ...

Recently, Quantitative Biology published an approach entitled “DeepDrug: A general graph-based deep learning framework for drug-drug interactions and drug-target interactions prediction ...