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The video of Guandao Yang discussing his paper "Geometry processing with Neural Fields" is up! YouTube Link: https://lnkd.in/dGqu2vcN I am excited to ...

With the right data fabric, people and algorithms can make better decisions and reduce the risk of data misuse or misinterpretation.

Graph data linked with geographic data will provide new means of data discovery, developers were told at a recent conference hosted by Esri.

Some of the modern GNNs have their roots in methods originally developed in the signal processing domain.   Graph Signal Processing started with two directions...

In the last couple of months, I’ve been noticing a gradual shift in the kind of articles that we receive at Data Science Central. We still get a fair amount of data science content, but increasingly (and admittedly with a bit of encouragement) we’re seeing more articles centered around graphs and semantics. I don’t believe… Read More »DSC Weekly Digest 22 February 2022: Graphology

It is nearly certain that, if you have ever played a 3D video game, watched a CGI-effects-laden movie, or seen increasingly hyperrealistic imagery, you have encountered a scene graph without realizing it. Scene graphs are pervasive in everything from media to medicine, from augmented reality to industrial digital twins, and they are increasingly playing an… Read More »Scene Graphs and Semantics

The Semantic Web has garnered a reputation for complexity among both Javascript and Python developers, primarily because, well, it’s not JSON, and JSON has become the data language of the web. Why learn some obscure language when JSON is perfectly capable of describing everything, right? Well, sort of. The problem that JSON faces, is actually… Read More »Why JSON Users Should Learn Turtle

How shape detection drives classification

Stardog Designer is our new, no-code, visual environment for data engineers and analysts to connect, map, model, and publish data. -- https://hubs.ly/...

𝖣𝖤𝖤𝖯 𝖫𝖤𝖠𝖱𝖭𝖨𝖭𝖦 𝖮𝖭 𝖦𝖱𝖠𝖯𝖧𝖲 332 Pages Free Pre-print download: https://lnkd.in/g7Eqg4Ag This book covers comprehensive contents in ...

With a $250,000 first prize, entrepreneurs, academics, engineers, scientists can create their own problem statement focused on a topic of their choosing.

We are proud to announce the release of ArangoDB 3.8! With this release ArangoDB improves many use-cases analytics.

Just because you’re calling your model a “knowledge graph” doesn’t make it so. True knowledge graphs possess three distinct characteristics.

Summary

You’ve probably seen web editors based on the idea of blocks. I’m typing this in WordPress, which has a little + button that brings up a long list of potential blocks that you can inser…

🧪 From an internal lab project to a project for the future of Dataveyes 🚀 We are very proud to introduce Modality, our analysis and visualisation tool... 36 comments on LinkedIn

Tim Berners-Lee has an interesting habit of coming up with ideas that seem hard to explain at the outset, remain all hard to understand even as they become more implemented and refined, can go for years with only a few die-hard fans becoming convinced that what he is doing is the best thing since sliced… Read More »How Solid Pods May End Up Becoming the Building Blocks of the Metaverse

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Graph databases will no longer be a luxury but will become a "must-have" for enterprise IT organizations in 2022, according to graph database provider TigerGraph. According to Gartner's research, by 2025, graph technologies will be used in 80% of new data and analytics systems, up from 10% in 2021, facilitating rapid decision-making across the enterprise.…

Nature Biotechnology - A knowledge graph platform integrates proteomics with other omics data and biomedical databases.

Pavel Klinov, Stardog VP of Research and Development, is back from the Dagstuhl Seminar on Graph Databases and Network Visualization, held at the Leibniz Center for Informatics in Germany from January 16 – 21, 2022. We asked him about his experience.

Leading researchers in Geometric & Graph ML summarise the progress in 2021 and make predictions for 2022

Rather than using mathematical graphs and relational databases, Dr. Hart explains the use and development of ontologies using everyday metaphorical scenarios.

Knowledge graphs are a powerful way to assist data scientists to crack hard data problems, but they aren’t as widely known as they could be. Graph database expert Maya Natarajan explains why that’s changing.

Graph Machine Learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships...

Can Machine Learning Do Symbolic Manipulation?  I spent some time over the holidays engaged in a fascinating online conversation. The gist of it was a variation of an argument that has been going on in the realm of artificial intelligence from the time of Minsky and Seymour Papert: Whether it is possible for neural networks to… Read More »DSC Weekly Digest 04 Jan 2022: Can Machine Learning Do Symbolic Manipulation?

How and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks. By Leo Meyerovich and Ben Lorica. [A version of this post originally appeared on the Graphistry blog.] In this post, we highlight the current state of Graph Intelligence, a new technology category around new tools and techniques forContinue reading "What is Graph Intelligence?"

AutoML on graphs is a thing. In the paper Automated Machine Learning on Graphs: A Survey (https://lnkd.in/djs25FfM), the authors present a comprehensive...

New Video! Zhaocheng Zhu explains his paper NeurIPS'21 paper "Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction...

Artificial Intelligence has a long history of oscillating between two somewhat contradictory poles. On one side, exemplified by Noam Chomsky, Marvin Minsky, Seymour Papert, and many others, is the idea that cognitive intelligence was algorithmic in nature – that there were a set of fundamental precepts that formed the foundation of language, and by extension,… Read More »Where Semantics and Machine Learning Converge