GraphNews

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:...

Check out all the latest stories, product features and special promo offers from Careem.

Deep Learning on Graphs for Natural Language Processing (DLG4NLP) is a very fast-growing area in recent years. Welcome to attend our DLG4NLP tutorial...

Devs: Semantic Web is so dead Amazon: provides a Linked Data API for Alexa with JSON-LD support https://t.co/ghLLiFOsWk

This article is an introduction into a field of graph-based code analysis. We will discuss a base concept of graph-based code analysis and learn how to build a Codebase Knowledge Graph (or Code Knowledge Graph or simply CKG) for a .NET Core project using Strazh.

The success of neural network embeddings has entailed a renewed interest in using knowledge graphs for a wide variety of machine learning and information retrieval tasks. In particular, recent...

Using knowledge-infused learning to integrate knowledge graphs and machine learning can lead to improvements in autonomous driving. Six grand opportunities.

Vesoft Inc. is planning a new funding round that could bolster the Chinese graph database technology startup’s valuation to almost $1 billion, according to its founder and Chief Executive Officer Sherman Ye.

Machine learning tools are used to greatly accelerate chip layout design, by posing chip floorplanning as a reinforcement learning problem and using neural networks to generate high-performance chip layouts.

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Fixing the talent pipeline so that finding rocket scientists doesn't have to be rocket science

Mapped, which simplifies access to building assets via a digital twin API, raised $6.5 million in a seed II round.

This is the first article in a four-part series on graph theory and graph neural networks. It explains graph theory in machine learning, and how it’s changed the game.

Our e-book aims to shed light on what we believe is a real game-changer for those looking to improve upon simplistic answers sometimes arrived at by using traditional ML algorithms and approaches. We show how you are able to combine the power of both graphs and ML (in a variety of different ways) to help you arrive at better answers compared to using standard ML approaches alone.

TigerGraph came out of stealth in 2017, and every year since has been coined “The Year of the Graph” by experts, journalists, and market watchers due to the accelerating momentum.  2018, 2019, and 2020 each had incremental “Year of the Graph” potential. In those years, more and more enterprises adopted graph at scale for increasingly […]