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Orbifold B.V.
Leuven, Belgium (Europe)
info@orbifold.net
orbifold.net
Beyond message passing, a physics-inspired paradigm for graph neural networks. https://t.co/viPTHXaPo4 #GraphMachineLearning https://t.co/BKqGJom5pz
Leo Meyerovich from @Graphistry on how and why the best companies are adopting Graph Visual Analytics, Graph AI, and Graph Neural Networks. https://t.co/GQNiKH9EJ4
#GraphAnalytics #GraphMachineLearning https://t.co/g3YYh8UcT2
#GraphAnalytics #GraphMachineLearning https://t.co/g3YYh8UcT2
TigerGraph Machine Learning Workbench is in preview and comes with a custom Jupyter Lab, plus lots of goodies to hook up your favorite graph ML framework. Exciting times ahead. @TigerGraphDB https://t.co/68Xe35GPOt #GraphMachineLearning https://t.co/2Lz0w5NuTm
My article on drug repurposing is now also published on the @TigerGraphDB blog. Thanks to the great Tigers and @CayleyWetzig in particular. https://t.co/uMV1aTvUrr
#healthcare #GraphMachineLearning #KnowledgeGraph https://t.co/inQbftYJGX
#healthcare #GraphMachineLearning #KnowledgeGraph https://t.co/inQbftYJGX
If you want to explore the knowledge graph visually in my latest article there is, besides yFiles (https://t.co/QR6wmzOJNS), also @Graphistry (https://t.co/IdqMN7NiNO) which manages to handle very large graphs in the blink of an eye.
#GraphVisualization
https://t.co/RzudOW7DKu https://t.co/CoDtw7RkAQ
#GraphVisualization
https://t.co/RzudOW7DKu https://t.co/CoDtw7RkAQ
Drug Repurposing Using TigerGraph & Graph Machine Learning. https://t.co/MdriWAJzJr #GraphAnalytics #KnowledgeGraphs
https://t.co/QuE2AoYAyk https://t.co/gGNlCQselk
https://t.co/QuE2AoYAyk https://t.co/gGNlCQselk
All paths lead to one. A Collatz graph visualization with 1.5 million nodes doesn't prove anything but certainly supports the conjecture. Layout based on custom Wolfram code. #GraphAnalytics
https://t.co/TBqkHzkp6U https://t.co/2WriphA2R4
https://t.co/TBqkHzkp6U https://t.co/2WriphA2R4