Microsoft’s Project Alexandria parses documents using unsupervised learning
GraphNews
Graph Database Startup Vesoft Seeks Funds at $1 Billion Value
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.
Acryl Data: we're live!
A graph placement methodology for fast chip design
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.
See Giorgia Lodi’s activity on LinkedIn
Sign in or join now to see posts like this one and more.
NASA reaches for graph DB to find people, skills for Moon and Mars missions
Fixing the talent pipeline so that finding rocket scientists doesn't have to be rocket science
Mapped raises $6.5M to build API for the ‘digital twin of data infrastructure’
Mapped, which simplifies access to building assets via a digital twin API, raised $6.5 million in a seed II round.
Why Graph Theory Is Cooler Than You Thought
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.
Connect the Dots: Harness the Power of Graphs & ML - OpenCredo
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.
The Decade of the Graph: 2021 Illustrates that Graph is entering the mainstream
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 […]
NASA is using data science to fill its data science skills gap
With data scientists in high demand, NASA is pursuing a pioneering approach to filling its skills gaps.
A unified view of Graph Neural Networks
Graph attention, graph convolution, network propagation are all special cases of message passing in graph neural networks.
Call for a Property Graph Schema Standard
Putting value on relationships.
ConviviaR Tools: Tagging the Scientific Abstracts with Wikidata Items
Here I am trying to build a script that process the short scientific texts (abstracts) and finds Wikidata items corresponding to the terms. An interactive and editable table is also created to allow an editor to validate the found matches and find other related items. A bit amateurish attempt by a Wikidata newbie.
Neo4j's $325 million venture suggests databases are cool again
Commentary: Relational databases aren't dead, but database innovation is cropping up in all sorts of places now, including graph databases.
Graph Machine Learning: Take graph data to the next level by applying machine learning techniques and algorithms.
Fridays give away! Graph Machine Learning: Take graph data to the next level by applying machine learning techniques and algorithms. Like and comment ... 75 comments on LinkedIn
Bruno Neri on LinkedIn: #graphneuralnetworks
"Very Deep Graph Neural Networks Via Noise Regularisation" by Petar Veličković, Yulia Rubanova, Alvaro Sanchez Gonzalez, Jonathan Godwin, et al. Paper...
Modelling Art Interpretation and Meaning. A Data Model for...
Iconology is a branch of art history that investigates the meaning of artworks in relation to their social and cultural background. Nowadays, several interdisciplinary research fields leverage...
Extraction of common conceptual components from multiple ontologies
We describe a novel method for identifying and extracting conceptual components from domain ontologies, which are used to understand and compare them. The method is applied to two corpora of...
Reimagining GNN Explanations with ideas from Tabular Data
Explainability techniques for Graph Neural Networks still have a long way to go compared to explanations available for both neural and decision decision tree-based models trained on tabular data....
Driving better decisions with knowledge graphs
Knowledge graphs are getting more mature and very practical in many different domains. From enabling data mesh architecture to disaster resilience, knowledge...
Social Network Analysis — Community Detection
Using R to extract user data from the Yelp API and create network graphs
NodePiece: Tokenizing Knowledge Graphs
Mapping each node to an embedding vector results in enormously large embedding matrices. Is there a way to have a fixed-size vocabulary of…
Social Network Analysis — Community Detection
Using R to extract user data from the Yelp API and create network graphs
Graph Self Supervised Learning: the BT, the HSIC, and the VICReg
Self-supervised learning and pre-training strategies have developed over the last few years especially for Convolutional Neural Networks (CNNs). Recently application of such methods can also be...
Michael Bronstein on LinkedIn: #GNNs #ICML2021
#GNNs are related to PDEs governing information diffusion on graphs. In a new #ICML2021 paper with Ben Chamberlain James Rowbottom Maria Gorinova Stefan...
A Voyage through Graph Machine Learning Universe: Motivation/Applications/Datasets/Graph ML…
SUMMARY
Aaron Bradley on LinkedIn: Introducing PathQuery, Google's Graph Query Language
There's a new query language in town, PathQuery - one "developed to scale with Google's query and data volumes as well as its internal developer community...
Harald Sack on Twitter
After your first steps with SPARQL we are now explaining more sophisticated SPARQL queries on the example of @wikidata in today's #ise2021 lecture#knowledgeGraphs #SemanticWebhttps://t.co/ZxxZftV7gd pic.twitter.com/I3T1TrX6P6— Harald Sack (@lysander07) June 18, 2021
BIS Conference on Twitter
3rd day of #BIS2021 started with a keynote presentation: Industrial #KnowledgeGraphs in Practice by Sonja Zillner from @siemens https://t.co/9K9BSRYqq0 pic.twitter.com/VR42aQOggQ— BIS Conference (@BISconf) June 16, 2021