GraphNews

Scientific Reports - Graph-based representation for identifying individual travel activities with spatiotemporal trajectories and POI data

Graph representations of programs are commonly a central element of machine learning for code research. We introduce an open source Python library python_graphs that applies static analysis to...

Ultipa: Reimagining Data Processing with Graph Augmented Intelligence Solutions/Service Company-Beijing, China; Singapore; California, U.S.A

Fine-tuning innovations from many vendors

Why provenance is the key to AI success

What are the three core features that give knowledge graphs their capabilities and how do they generate value for four key players?

NNeo4j, JanusGraph, and TigerGraph are the top 3 Native Property Graph Database Management Systems, according to DB-Engines ranking, but…

Thoughts on semantic layers, data transformations, data apps and the future of the data stack.

AWS developed the Deep Graph Knowledge Embedding Library (DGL-KE), a knowledge graph embedding library built on the Deep Graph Library (DGL). DGL is a scalable, high performance Python library for deep learning in graphs. This library is used by the advanced machine learning systems developed with Trumid to build a credit trading platform.

In a distributed world where data is federated in a Mesh internally and you value comes from how you collaborate externally the most…

Happy to announce that we just published our #linkeddata extension for #VSCode. Visualize, transform, validate and query your #rdf directly on your files...

Posted Grigor Aslanyan, Software Engineer, Google Patent documents typically use legal and highly technical language, with context-depend...

At IKEA we are building a knowledge graph to improve the overall experience of our customers in the physical and digital space. I like to…

You thought you knew all normal forms? Well, think again: There is also “graph normal form,” based on mathematics going back 25 years.

Co-authored with Meghana Negi, Jose Mathew, Jairaj Sathyanarayana

Ultipa has recently released v4.0 of its flagship graph database product, on top of its v3.0’s already worldleading performance. Ultipa 4.0 introduced p

Recent advancements and hot trends, July 2022 edition

Network architecture plays a key role in the deep learning-based computer vision system. The widely-used convolutional neural network and transformer treat the image as a grid or sequence...

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

Today we’ll dive into the theory and implementation of the Graph Attention Network (GAT). In a nutshell: attention rocks, graphs rock…

Feature Propagation is a simple and surprisingly efficient solution for learning on graphs with missing node features

It was a thing long before big tech firms used it to work out who knew who, explains AWS

Signal AI unveiled its new tool, a data structure that constantly tracks the major and minor events for companies that course through the news sphere each day.

Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics. — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national

Data Commons brings together sustainability-related data from over 100 sources — on everything from temperature to water availability.

Announcing my new (FREE) course: Basics of Graph Neural Networks (https://lnkd.in/gkP2VNYz). The focus is to give you a fast, high-level overview of common... 12 comments on LinkedIn