Sahil Dua discusses the critical role of embedding models in powering search and RAG applications at scale. He explains the ...

Mass General Brigham researchers are betting that the next big leap in brain medicine will come from teaching artificial ...

In an interview with Technology Networks, Dr. Daniel Reker discusses how machine learning is improving data-scarce areas of ...

This research presents a comprehensive framework for constructing and applying student portraits in personalized education through advanced data analytics and knowledge graph technology. The study ...

Abstract: Cross-domain remaining useful life prediction is a critical task for industrial applications, and existing domain adaptation (DA) techniques typically focus on mitigating domain shift by ...

Circular RNAs (circRNAs) are a unique class of non-coding RNAs with stable covalently closed structures that play key regulatory roles in gene expression and drug response. However, experimental ...

What are the phases for Global Learning participation? The Global Learning application process is a two-step process, and participation is contingent upon approval by Santa Clara University. Phase 1: ...

The identification of wheat infections has always been a considerable problem in agricultural forecasting. This paper presents an automated classification framework for wheat illnesses utilising ...

Abstract: Contrastive learning, as an efficient unsupervised learning, has been extensively studied for improving graph neural network (GNN) in graph-structured data mining. With the wider application ...

Jerrid Kruse receives funding from the National Science Foundation, the NASA Iowa Space Grant Consortium, and the William G. Stowe Foundation. During my years teaching science in middle school, high ...