Overview of Graph Attention Networks (GAT)

Overview of Graph Attention Networks (GAT)

Author: Deng Yang This article is approximately 6300 words long and is recommended for a 10-minute read. This article briefly introduces the working principles of GAT based on the order discussed in the paper by Velickovic et al. (2017). When numbers are intangible, intuition is sparse; when forms are few, it is hard to delve … Read more

Exploring Neural Algorithm Reasoning in Graphs

Exploring Neural Algorithm Reasoning in Graphs

Developing artificial intelligence systems with advanced reasoning capabilities is a long-standing research problem. Traditionally, the main strategy for addressing this challenge involves the use of symbolic methods, where knowledge is explicitly represented through symbols and implemented through explicitly programmed rules. However, with the emergence of machine learning, systems have shifted towards being able to learn … Read more