Generative Artificial Intelligence

Description

This course introduces the theoretical foundations and practical implementations of generative artificial intelligence. Building upon probabilistic modeling principles, students will study deep generative models including VAEs, GANs, autoregressive models, diffusion models, and flow-based models. The course also covers text, image, and multimodal generation systems, with an emphasis on research paper reading and project-based applications. Projected Results: 1. Develop a systematic understanding of the mathematical foundations of generative AI. 2. Compare and select appropriate generative models for different applications. 3. Conduct research-level generative modeling projects.