Click on the above“Visual Learning for Beginners”, select to add a star or “pin” Heavyweight insights delivered in real-time Author: Compiled by: ronghuaiyang Introduction The aim of this perspective is to build intuition behind the Transformer architecture in NLP and its connection to Graph Neural Networks. Engineer friends often ask me: “Graph deep learning” sounds … Read more
This article is about 4500 words long and is recommended for a reading time of over 10 minutes. This article introduces Graphormer, a graph representation learning method based on the standard Transformer architecture. 1 Introduction The Transformer architecture has shown excellent performance in fields such as natural language processing and computer vision, but it performs … Read more
This article is a transcript of the live sharing session by Wang Hongwei, a PhD student from Shanghai Jiao Tong University and intern at Microsoft Research Asia, on January 10 during the 23rd PhD Talk. Network representation learning (network embedding) has emerged in recent years as a branch of feature learning research. As a dimensionality … Read more