학술행사
Geometric Deep Learning and Its Applications
등록일자 : 2024-05-30- 발표자 김동우 교수(포항공과대학교)
- 조직위원 산업수학혁신센터
- 기간 2024-06-13 ~ 2024-06-13
- 장소 판교 테크노밸리 산업수학혁신센터 세미나실
- 주최 산업수학혁신센터
1. 시간: 14:00~16:00
2. 경기 성남시 수정구 대왕판교로 815, 기업지원허브 231호 국가수리과학연구소
3. 무료주차는 2시간 지원됩니다.
Geometric deep learning has recently gained increasing attention, sparked by advances in graph neural networks. In the first part of this talk, I will explain the basic mechanism behind message passing propagation neural networks (MPNN) and discuss their expressivity in terms of the graph isomorphism test. In the second part of this talk, I will briefly introduce other aspects of geometric deep learning related to different geometric structures, such as non-Euclidean manifolds and point clouds. I will discuss how these structures can be effectively utilized in deep learning frameworks and highlight the unique challenges and opportunities they present.
*유튜브 스트리밍 예정입니다.
1. 시간: 14:00~16:00
2. 경기 성남시 수정구 대왕판교로 815, 기업지원허브 231호 국가수리과학연구소
3. 무료주차는 2시간 지원됩니다.
Geometric deep learning has recently gained increasing attention, sparked by advances in graph neural networks. In the first part of this talk, I will explain the basic mechanism behind message passing propagation neural networks (MPNN) and discuss their expressivity in terms of the graph isomorphism test. In the second part of this talk, I will briefly introduce other aspects of geometric deep learning related to different geometric structures, such as non-Euclidean manifolds and point clouds. I will discuss how these structures can be effectively utilized in deep learning frameworks and highlight the unique challenges and opportunities they present.
*유튜브 스트리밍 예정입니다.
