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[2102.13085] Towards Robust Graph Contrastive Learning
[2102.13085] Towards Robust Graph Contrastive Learning
We study the problem of adversarially robust self-supervised learning on graphs. In the contrastive learning framework, we introduce a new method that increases the adversarial robustness of the...
#KnowledgeGraph
·arxiv.org·
[2102.13085] Towards Robust Graph Contrastive Learning
What is RDF-Star? - Ontotext
What is RDF-Star? - Ontotext
A detailed definition with examples for RDF-Star (also known as “RDF*”), which allows descriptions to be added to edges in a graph.
#KnowledgeGraph
·ontotext.com·
What is RDF-Star? - Ontotext
Learning SPARQL on Twitter
Learning SPARQL on Twitter
160 SPARQL endpoints, indexing of stuff in GitHub repositories: interesting work by Vincent Emonet at @UM_IDS: https://t.co/6Jh93YEvRP (file PRs for missing resources here: https://t.co/M5d94NgIrn)— Egon Willighⓐgen (@egonwillighagen) February 27, 2021
#KnowledgeGraph
·twitter.com·
Learning SPARQL on Twitter
From Knowledge Graphs to Knowledge Workflows | Diffblog
From Knowledge Graphs to Knowledge Workflows | Diffblog
2020 Was The “Year of the Knowledge Graph” 2020 was undeniably the “Year of the Knowledge Graph.” 2020 was the year that Gartner put Knowledge Graphs at the peak of its hype cycle. It was the year where 10% of the papers published at EMNLP referenced “knowledge” in their titles. It was the year over […]
#KnowledgeGraph
·blog.diffbot.com·
From Knowledge Graphs to Knowledge Workflows | Diffblog
AKSW on Twitter
AKSW on Twitter
New @orkg_org release today featuring a new contribution editor, where you can directly add a comparison table to capture the state-of-the-art for a particular research problem: https://t.co/nhZ7Gjzilh pic.twitter.com/MJmLp9bvIi— Sören Auer (@SoerenAuer) March 8, 2021
#GraphAnalytics#KnowledgeGraph
·twitter.com·
AKSW on Twitter
Learning SPARQL on Twitter
Learning SPARQL on Twitter
“This library provides a prolog interface to SPARQL queries. It allows logic program queries to be compiled to SPARQL, and then executed on a remote SPARQL server.” https://t.co/3YaKL1AJkq— Learning SPARQL (@LearningSPARQL) March 8, 2021
#KnowledgeGraph
·twitter.com·
Learning SPARQL on Twitter
The Rise of Graph Technology
The Rise of Graph Technology
Although artificial intelligence capabilities are improving daily, it is not always easy to put the AI rubber on the road – especially when it comes to understanding AI’s contextual data and problem-solving approaches. How about bringing in some “real” intelligence? Graphs are a typically human way
#GraphDB#GraphAnalytics#KnowledgeGraph
·linkedin.com·
The Rise of Graph Technology
Torn Between UUIDs and Friendly IRIs? Use Both!
Torn Between UUIDs and Friendly IRIs? Use Both!
Having been involved in the Semantic space for more than a decade and a half, I've seen quite a few arguments that seem to be eternal. Do you use upper ontologies or not? Is SHACL better than OWL? Property Graphs vs.
#KnowledgeGraph
·linkedin.com·
Torn Between UUIDs and Friendly IRIs? Use Both!
model the interactions between drugs and various biological targets in the body to predict which ones could be used for the treatment of Covid-19. I framed the problem as edge regression on a bipartite graph, and used a variant of graph convolutional networks to predict over 50 potential Covid-19 treatments.
model the interactions between drugs and various biological targets in the body to predict which ones could be used for the treatment of Covid-19. I framed the problem as edge regression on a bipartite graph, and used a variant of graph convolutional networks to predict over 50 potential Covid-19 treatments.
I'm so excited to share this! 🚀✨ My latest research project was to model the interactions between drugs and various biological targets in the body to... 15 comments on LinkedIn
#GraphAI#KnowledgeGraph
·linkedin.com·
model the interactions between drugs and various biological targets in the body to predict which ones could be used for the treatment of Covid-19. I framed the problem as edge regression on a bipartite graph, and used a variant of graph convolutional networks to predict over 50 potential Covid-19 treatments.