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 designed to ...

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. For ...

Why is the language developers and DBAs use to organize data such a mess? Here are 13 reasons we wish we could quit SQL, even ...

ClickUp is an attractive work management solution with a ton of features, especially for collaborative document creation, but ...

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

About Context-Aware RAG library for Knowledge Graph ingestion and retrieval functions.

The rise of memecoins proves that attention is the most valuable commodity in crypto. Memecoins lower the barriers to entry in crypto by wrapping speculation ...

As Dr. García-Pavia will elaborate, while aficamten improved exercise capacity, metoprolol resulted in a meaningful reduction in exercise capacity. Treatment with aficamten also produced larger ...

Agile rituals are great, but without tracking constraints and dependencies live, your transformation will stall.

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 ...