Bitcoin returns and volatility are falling, leading researchers to say “values above $1 million will probably take 15 years.” ...

Since its introduction by Microsoft in 2024 as a way to address the limitations of large language models, GraphRAG has emerged as a leading method for focusing LLM reasoning and delivering accurate, ...

As the self-quantification movement matures, users are expanding beyond physical tracking to assess how they think, decide, ...

With the rapid advancements in computer technology and bioinformatics, the prediction of protein-ligand binding sites has ...

Learn how Neo4j and n8n simplify knowledge graphs for smarter data insights. Build AI-driven graphs for customer data and document navigation ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

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 ...

The growing availability of spatial transcriptomics data offers key resources for annotating query datasets using reference datasets. However, batch effects, unbalanced reference annotations, and ...

Abstract: Graph Contrastive Learning (GCL) plays a crucial role in multimedia applications due to its effectiveness in analyzing graph-structured data. Existing GCL methods focus on maximizing the ...