As AI demand outpaces the availability of high-quality training data, synthetic data offers a path forward. We unpack how synthetic datasets help teams overcome data scarcity to build production-ready ...

Graph neural networks (GNN) rely on graph operations that include neural network training for various graph related tasks. Recently, several attempts have been made to apply the GNNs to functional ...

Grok 3 has caught up with its competitors, but is it enough to convert ChatGPT users? Credit: Matteo Della Torre / NurPhoto / Getty Images Now that Grok 3 from Elon Musk's xAI is officially live, how ...

Before installation, it’s crucial to understand that Microsoft Graph is a RESTful web API that integrates various Microsoft services. You only need to authenticate once to access data across these ...

This guide explains what Microsoft Graph Explorer does and how you can use it to test Microsoft Graph API requests quickly. You will learn how to open it, run queries, adjust permissions, view code ...

This important work introduces a family of interpretable Gaussian process models that allows us to learn and model sequence-function relationships in biomolecules. These models are applied to three ...

Abstract: Graph condensation reduces the size of large graphs while preserving performance, addressing the scalability challenges of Graph Neural Networks caused by computational inefficiencies on ...

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 ...

Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...