Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:	孙剑教授，西安交通大学数学与统计学院
Inviter:	陈冲副研究员
Title:	Deep Learning in Non-Euclidean Space
Time & Venue:	2021.10.18 15:00-16:30 腾讯会议ID：779 919 771 入会密码：311311
Abstract:	会议链接：https://meeting.tencent.com/dm/nkts0pJkwVNo The traditional deep networks are commonly defined in Euclidean space, either in the 3D / 2D image space or sequential data space. However, in realistic scenario, the data maybe irregular or distributed on manifold / graph. In such cases, the traditional deep network does not fully take advantages of the underlying data structure in non-Euclidean space. Along this research direction, in this talk, I will introduce the research backgrounds, advances in research on geometric deep learning approach in the non-Euclidean space, with applications to 3D object recognition, image segmentation and domain adaptation.