Abstract: Learning embeddings for entities and relations in knowledge graph (KG) have benefited many downstream tasks. In recent years, scoring functions, the crux of KG learning, have been human ...

Abstract: Knowledge graph embedding is an effective way to represent knowledge graph, which greatly enhance the performances on knowledge graph completion tasks, e.g., entity or relation prediction.

Geedge Networks, a company with ties to the founder of China’s mass censorship infrastructure, is selling its censorship and ...

Embrace city science as a vital partner in architecture, merging creativity with data to build resilient and equitable urban ...

Optimization and architecture definition in chip design is important, but there's a downside to too much customization.

PFIX provides convex exposure to rising long-term rates via payer swaptions, making it a strong hedge in volatile, steepening ...

Context Aware RAG is a flexible library designed to seamlessly integrate into existing data processing workflows to build customized data ingestion and retrieval (RAG) pipelines. With Context Aware ...

University life can be expensive. Many apps can help students manage money. Starling Bank offers budgeting tools. Curve ...

The all-new Coros Nomad watch has a built-in microphone for recording rugged off-grid adventures, but the price is the real ...

This study illustrates a valuable application of BID-seq to bacterial RNA, allowing transcriptome-wide mapping of pseudouridine modifications across various bacterial species. The evidence presented ...

Achieving a high OEE score has been elusive in the past as processors grapple with where to begin in troubleshooting OEE ...

Missense variants in the O-GlcNAc transferase ( OGT) gene have recently been shown to segregate with a syndromic form of intellectual disability (OGT-ID), underscoring the importance of protein ...