Businesses need streaming ingestion tools and centralized data lakes with separate storage and compute layers to fulfill customer requests.

Graph Kernel Attention Transformers: Toward Expressive and Scalable Graph Processing | Synced...

Common sense knowledge graph embedding projected fasttext document embeddings vs transformers In these two blog posts, Radix demonstates deep learning...

Graphs algorithms, which are ideal to analyze sparse and irregular datasets, can benefit from special hardware that optimizes their performance.

While graph databases like Neo4j are schemaless by default, leverage the power of schemas in development by focusing on application driven graph schema design

Until very recently, the objects of common use such as wearable devices, cars, watches, refrigerators and health-monitoring devices, did not produce or handle d

Learning Attributed Graph Representations with Communicative Message Passing Transformer • Constructing appropriate representations of molecules lies at...

Leveraging the network structure of the use case to boost predictive performance

The application of graph analytics to various domains have yielded tremendous societal and economical benefits in recent years. However, the increasingly widespread adoption of graph analytics...

How do knowledge graphs influence artificial intelligence? Here's how looking at the relat

A hands-on overview with a real world dataset

As our world grows increasingly digital, for all the good, there’s also all the bad. Financial criminals are no longer stuffing suitcases and running the goods through “legitimate” businesses; they’re taking down significant portions of financial institutions with a few strokes of the keyboard. According to EY, “The estimated annual cost of money laundering and […]

I wrote on this topic way back in 2016, but when a recent reader indicated that the original article didn't have images anymore (it happens), it seemed like a good opportunity to write about it again. I am Kurt Cagle, or, according to my birth certificate, Kurt Alan Cagle.

The increasing digitalization of the manufacturing domain requires adequate knowledge modeling to capture relevant information. Ontologies and Knowledge Graphs provide means to model and relate a...

As organizer of the WAIC European Online Forum, Expand.hk would like to thank six distinguished speakers:  Gadi Singer, Walid Saba, Dr. Keith Duggar, ...

Step by step examples for working with and evolving FIBO Vocabulary. Includes analysis of different option and a download file for the recommended approach.

By now, we have an understanding of what a graph is and learned some of the methods in traversing them.

I'm excited to share that I've joined the #netflix Content Data Science & Engineering, leadership team! In my new role, I'll be leading the Content Knowledge... 58 comments on LinkedIn

This summer I've been mentoring two summer interns at Capgemini, Stian Teien and Andreas Mathisen. They have been working on a semantic knowledge graph...

Graph Neural Networks User Group

The 2021 Knowledge Graph Conference, held online May 3–6, had over 1000 people attending. Special thanks to all of the 20+ people who…

In this article, we introduce Deep Learning Graphs and go through 7 up-and-coming open-source libraries for graph deep learning, ranked in order of ...

A few slides on the applications of Graph Neural Networks https://lnkd.in/gyvkHrr...

he high-performance graph database solution provider, Ultipa, secures $21M in Series-A financing led by a well-known sovereign fund, and its angel investor, CM

Interested in explainability for graph neural networks? Check out this list created by our team in AstraZeneca (Gavin E. and Sebastian Nilsson)! https:...

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