Convolutional Neural Networks on Graphs

Speaker:        Dr. Xavier Bresson
                Nanyang Technological University

Title:          "Convolutional Neural Networks on Graphs"

Date:           Monday, 10 December 2018

Time:           11:00am to 12 noon

Venue:          Lecture Theater H (near lifts 27/28), HKUST


In the past years, deep learning methods have achieved unprecedented
performance on a broad range of problems in various fields from computer
vision to speech recognition. So far research has mainly focused on
developing deep learning methods for grid-structured data, while many
important applications have to deal with graph-structured data. Such
geometric data are becoming increasingly important in computer graphics
and 3D vision, sensor networks, drug design, biomedicine, recommendation
systems, and web applications. The purpose of this talk is to introduce
the emerging field of deep learning on graphs, overview existing solutions
as well as applications for this class of problems.

NIPS'17: Geometric Deep Learning on Graphs,

UCLA'18: New Deep Learning Techniques,


Xavier Bresson (PhD 2005, EPFL, Switzerland) is Associate Professor in
Computer Science and member of the Data Science and AI Research Centre at
NTU, Singapore. He is a leading researcher in the field of graph deep
learning, a new framework that combines graph theory and deep learning
techniques to tackle complex data domains in neuroscience, genetics,
social science, physics, and natural language processing. In 2016, he
received the highly competitive Singaporean NRF Fellowship of 2.5M US$ to
develop these new learning techniques. He was also awarded several
research grants in the U.S. and Hong Kong. He has published more than 60
peer-reviewed papers, including NIPS, ICML, ICLR, JMLR. He has organized
international workshops and tutorials on deep learning in collaboration
with Facebook, NYU, and USI such as the 2018 UCLA workshop, the 2017 CVPR
tutorial and the 2017 NIPS tutorial. He has been teaching undergraduate,
graduate and industrial courses in data science and deep learning at EPFL
(Switzerland), NTU (Singapore) and UCLA (U.S.).