GraphNews

Excited to share a Colab tutorial on graph neural networks with the JAX+Jraph stack, which we use in-house at DeepMind! Developed by Lisa Wang and Nikola... 12 comments on LinkedIn

"The Open Application Group (OAGi) and the Industrial Ontologies Foundry (IOF) have signed an agreement to produce industrial ontologies." [PR] https://t.co/zz511UBuYE— Aaron Bradley (@aaranged) March 3, 2021

Identifying Ingredient Substitutions Using a Knowledge Graph of Food https://t.co/5pZWc9Bt94 pic.twitter.com/PgkMr9idHj— Aaron Bradley (@aaranged) March 3, 2021

Introduction to timbr and the Covid-19 SQL knowledge graph

Excited that our graph Transformer has been accepted as a Contributed Talk to NeurIPS ML and Physical Sciences workshop (TOP 3 out of 151) :D Thanks to...

Why enterprise ontology management matters to the EKG industry

Our work has been published in Nature!!! (G)NNs can successfully guide the intuition of mathematicians & yield top-tier results -- in both representation... 48 comments on LinkedIn

Last week Google added Graph Neural Network support to TensorFlow. This comes in the wake of PyTorch Geometric getting a lot of support from Meta (formerly...

[DevFest Casablanca 2021 Speakers 😎] Anas AIT AOMAR, Engineering Student at Emines school of industrial management. who also payback to the community...

After years of writing a graph data science blog, I've decided to present all my learning in a more guided and structured way. Today I am happy to announce...

Earlier this month I asked here on LinkedIn about interest publishing a short piece on Knowledge Graphs. The response was overwhelmingly positive, so today...

G.V() is an all-in-one Gremlin IDE to write, test and analyze results for your TinkerPop-enabled graph database - in open beta now and looking for feedback: https://t.co/0FLK7kC9K9 #graphdb pic.twitter.com/7U8PeKFsm9— TinkerPop (@apachetinkerpop) November 22, 2021

How to tune the hyperparameters of FastRP to your specific problem

New perspectives on old problems in Graph ML

Beyond listing superficial benefits and implications: Let’s explore what the fundamental difference of the two is.

Learn more about content hubs and how to build them by leveraging deep learning and data in a knowledge graph and using a specific technique called knowledge graph embeddings (or simply KGE).

Your regular digest of KG research, November edition

By Matthias Müller, Head of Embodied AI Lab at Intel Labs Matthias Mueller leads the Embodied AI Lab at Intel Labs, where he and his team develop algorithms pertaining to the fields of robotics, computer vision, graphics, and machine learning. The goal of Intel Labs’ Embodied AI Lab is to build inte

Swedish unicorn Neo4j counts the likes of Adobe, AstraZeneca, Comcast, Ebay, and UBS among its growing clientele.

Sometime I become so addicted to a particular framework that I completely forget about how the world is changing out there. Therefore…

Papers With Code highlights trending Machine Learning research and the code to implement it.

Learning to execute algorithms is a fundamental problem that has been widely studied. Prior work~\cite{veli19neural} has shown that to enable systematic generalisation on graph algorithms it is...

The number of users approaching the world of cryptocurrencies exploded in the last years, and consequently the daily interactions on their underlying distributed ledgers have intensified. In this...

Let’s understand how to optimize GRL models and their ability to incorporate different network features

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Can GraphQL scale beyond workgroups or departments? Changes to Apollo GraphQL's federation gateway should make GraphQL better suited for enterprise scale adoption.

My keynote at CIKM 2021 workshop on Knowledge Injection in Neural Networks--about uses/misuses of #LLMs, importance of explicit knowledge, and our ongoing...