[D] Beyond Message Passing: a Physics-Inspired Paradigm for Graph Neural Networks

Web: https://www.reddit.com/r/MachineLearning/comments/uly03x/d_beyond_message_passing_a_physicsinspired/

Hi there, The Gradient has a new article that many of you might find interesting - [Beyond Message Passing: a Physics-Inspired Paradigm for Graph Neural Networks](https://thegradient.pub/graph-neural-networks-beyond-message-passing-and-weisfeiler-lehman/) .

>The message-passing paradigm has been the “battle horse” of deep learning on graphs for several years, making graph neural networks a big success in a wide range of applications, from particle physics to protein design. From a theoretical viewpoint, it established the link to the Weisfeiler-Lehman hierarchy, allowing to analyse the expressive power …

graph graph neural networks machinelearning networks neural neural networks physics