Yasunari Suzuki1,2, Yoshiaki Kawase3, Yuya Masumura4, Yuria Hiraga5, Masahiro Nakadai6, Jiabao Chen7, Ken M. Nakanishi7,8, Kosuke Mitarai3,7,9, Ryosuke Imai7, Shiro Tamiya7,10, Takahiro Yamamoto7,...

Graph theory isn’t enough. The mathematical language for talking about connections, which usually depends on networks — vertices (dots) and edges (lines connecting them)...

This blog is a part of my “deep learning update” series and I want to open it up with a question: What have I learned...

playcircle Scaling Laws for Language Transfer Learning Christina Kim OpenAI Mentor: Jerry TworekPrevious Roles: Founding Engineer at Sourceress, Research Fellow at Recurse Center,...

With a record high of 9034 research papers submitted to AAAI 2021 and an acceptance rate of 21%, a total of 1692 papers...

This article describes how to extend the simplest formulation of Graph Neural Networks (GNNs) to encode the structure of multi-relational data, such as...

Graph Neural Networks (GNNs) have emerged as the standard toolbox to learn from graph data. GNNs are able to drive improvements for high-impact...

This blog is based on the paper A Generalization of Transformer Networks to Graphs with Xavier Bresson at 2021 AAAI Workshop on Deep Learning on Graphs: Methods and...

At the beginning of the year, I have a feeling that Graph Neural Nets (GNNs) became a buzzword. As a researcher in this...

How open banking is driving huge innovation Learn how fintechs and forward-thinking FIs are accelerating personalized financial...

This blog is a comprehensive overview of the challenges of data extraction from a Passport using OCR technologies and possible solutions.In several organizations,...

Graph Neural Networks extend the learning bias imposed by Convolutional Neural Networks and Recurrent Neural Networks by generalising the concept of “proximity”, allowing...