Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
TigerGraph, provider of a leading graph analytics platform, is introducing the TigerGraph ML (Machine Learning) Workbench—a powerful toolkit that enables data scientists to significantly improve ML ...
Jan. 19, 2024 — Solving today’s most complex scientific challenges often means tracing links between hundreds, thousands or even millions of variables. The larger the scientific dataset, the more ...
As a topic editor (TE), you will take the lead on all editorial decisions for the Research Topic, starting with defining its scope. This allows you to curate research around a topic that interests you ...
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 ...
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A group of scientists has created a neural network based on polymeric memristors -- devices that can potentially be used to build fundamentally new computers. These developments will primarily help in ...