Graph neural networks (GNNs) have emerged as a powerful framework for analyzing and learning from structured data represented as graphs. GNNs operate directly on graphs, as opposed to conventional ...
TigerGraph, provider of a leading graph analytics platform, is introducing the TigerGraph ML (Machine Learning) Workbench—a powerful toolkit that enables data scientists to significantly improve ML ...
Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...
How would you feel if you saw demand for your favorite topic — which also happens to be your line of business — grow 1,000% in just two years’ time? Vindicated, overjoyed, and a bit overstretched in ...
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More What do you get when you combine two of the most up-and-coming paradigms ...
A graphene-based memory resistor (memristor) that can exist in many different states has been designed and demonstrated by Thomas Schranghamer, Aaryan Oberoi and Saptarshi Das at Pennsylvania State ...
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