Graph Neural Network News Today

<p>The work provides a new clue for constructing GRNs, and proposed framework GRINCD also shows potential in identifying key factors affecting cancer development.</p>

Gene regulatory networks (GRNs) depict the regulatory mechanisms of genes within cellular systems as a network, offering vital insights for understanding cell processes and molecular interactions that determine cellular phenotypes.

A new project to improve the processing speed of neural networks on Apple Silicon is potentially able to speed up training on large datasets by up to ten times.

A new project to improve the processing speed of neural networks on Apple Silicon is potentially able to speed up training on large datasets by up to ten times.

To kick-start the new Research Priority Area (RPA) of the Faculty of Science in "Artificial Intelligence for Sustainable Molecules and Materials" (AI4SMM), four projects have just been launched. Combining the Faculty’s strengths in computer science and sustainability research, AI4SMM aims to develop and use machine learning techniques for the design of molecules and materials for a sustainable future. The projects cover topics as diverse as metamaterials for sustainable steel, and pr...

The two-tower (or twin-tower) embedding model connects embeddings in two different modalities by placing both modalities in the same vector space

/PRNewswire/ -- Kumo, a leading deep learning platform for relational data, today announced at Snowflakes annual user conference, Snowflake Summit 2023, that...

JABSOM researchers are making advancements in biochemical reaction network analysis.

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Graph neural networks (GNNs) are now the mainstream method for mining graph-structured data and learning low-dimensional node- and graph-level embeddings to serve downstream tasks. However, limited by the bottleneck of interpretability that deep neural networks present, existing GNNs have ignored the issue of estimating the appropriate number of dimensions for the embeddings. Hence, we propose a novel framework called Minimum Graph Entropy principle-guided Dimension Estimation, i.e. MGEDE, that ...