Game-Theoretic Diffusion Models
- 2025-03-10 (Mon.), 10:30 AM
- 統計所B1演講廳;茶 會:上午10:10。
- 實體與線上視訊同步進行。
- Dr. Ya-Ping Hsieh
- ETH Foundations of Data Science, Switzerland
Abstract
AI systems have significant potential to drive progress in both industrial and scientific domains, particularly in areas such as AI-assisted drug discovery. However, conventional AI models often operate within static and single-agent decision-making frameworks, limiting their adaptability to complex, real-world challenges.
In this talk, I will discuss the fundamental limitations of these existing frameworks and present algorithmic approaches designed to address them. I will then introduce a research project focused on integrating multi-agent paradigms and dynamic modeling, aiming to enhance the practical effectiveness of future AI systems by bridging the gap between theoretical foundations and real-world complexities.
線上視訊請點選連結