Stanford CME296: Diffusion & — Stanford Online

This course explores diffusion-based generative models for vision. You will study the foundations of diffusion, score matching and flow matching, modern architectures such as Diffusion Transformers, and methods for controllable image generation and evaluation. The course combines theory with practical insights into state-of-the-art generative models. Ideal for students with a background in linear algebra, probability, calculus, and machine learning. Learn more and enroll: https://online.stanford.edu/courses/cme296-diffusion-and-large-vision-models View the course syllabus: https://cme296.stanford.edu/syllabus/ Afshine Amidi is an Adjunct Lecturer at Stanford University. Shervine Amidi is an Adjunct Lecturer at Stanford University.

Aulas do Curso (8 vídeos)

0 de 8 aulas concluídas 0%

Progresso salvo somente neste navegador.

Sobre o Canal

Stanford Online

You can gain access to a world of education through Stanford Online, the Stanford School of Engineering’s portal for academic and professional education offered by schools and units throughout Stanford University. https://online.stanford.edu/ Our robust catalog of degree programs, credit-bearing education, professional certificate programs, and free and open content is developed by Stanford faculty, enabling you to expand your knowledge, advance your career, and enhance your life. Stanford Online is operated and managed by the Stanford Engineering Center for Global & Online Education (CGOE). CGOE expands access to Stanford teaching and research, working in collaboration with faculty in the School of Engineering and throughout Stanford University to design and deliver extensive global, online, and enterprise education to a global audience.