일시: 2023년 9월 7일(목), 14:00-16:00
장소: 판교 테크노밸리 산업수학혁신센터 세미나실
발표자: 홍영준 교수(카이스트)
주요내용: Toward bridging a connection between machine learning and applied mathematics
This lecture explores the topics and areas that have guided my research in computational mathematics and deep learning in recent years. Numerical methods in computational science are essential for comprehending real-world phenomena, and deep neural networks have achieved state-of-the-art results in a range of fields. The rapid expansion and outstanding success of deep learning and scientific computing have led to their applications across multiple disciplines. In this lecture, I will focus on connecting machine learning with applied mathematics, specifically discussing topics such as adversarial examples, generative models, and scientific machine learning.
*유튜브 스트리밍 예정입니다.
일시: 2023년 9월 7일(목), 14:00-16:00
장소: 판교 테크노밸리 산업수학혁신센터 세미나실
발표자: 홍영준 교수(카이스트)
주요내용: Toward bridging a connection between machine learning and applied mathematics
This lecture explores the topics and areas that have guided my research in computational mathematics and deep learning in recent years. Numerical methods in computational science are essential for comprehending real-world phenomena, and deep neural networks have achieved state-of-the-art results in a range of fields. The rapid expansion and outstanding success of deep learning and scientific computing have led to their applications across multiple disciplines. In this lecture, I will focus on connecting machine learning with applied mathematics, specifically discussing topics such as adversarial examples, generative models, and scientific machine learning.
*유튜브 스트리밍 예정입니다.