1. 일시: 2024.6.13.(목), 14:00~16:00 2. 장소: 판교 테크노밸리 산업수학혁신센터 세미나실 3. 경기 성남시 수정구 대왕판교로 815, 기업지원허브 231호 국가수리과학연구소 - 무료주차는 2시간 지원됩니다. 4. 발표자: 김동우 교수 (포항공과대학교) 5. 주요내용: Geometric Deep Learning and Its Applications 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.**