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Course Description and Objectives
The course may be given in English or French depending on the audience’s preferences.
- Applied Mathematics (Linear Algebra, Numerical Analysis, Differential Calculus, Fourier Analysis) Programming (Python, Matlab)
- Basic concepts of image processing, optimization and deep learning are useful but will be introduced in the course.
- Individual reports of Practical Work (TPs).
- Individual project with report and oral defense at the end of the course.
Organization of the course
- 7 sessions of 3 hours each (course+TP) + 2 review sessions + 1 project presentation session
- Dates & venue: every Thursday from 2pm to 5pm, in room 5B01 at Telecom Paris, 19 place Marguerite Perey F-91120 Palaiseau.
Important: For the practical sessions starting on January 23rd, students will need a computer account at Telecom ParisTech. If you do not have one you should go to this site and follow the instructions to obtain your account.
- End-to-end deep learning and applications to super-resolution (S. Ladjal, 1 course + 1 TP)
- Inverse problems, variational, statistical and hybrid methods (A. Almansa, 1 course + 1 TP)
- Generative models for texture synthesis (S. Ladjal, 1 course+TP)
- Variational Auto Encoders (A. Newson, 1 course + TP)
- Generative Adversarial Networks (A. Newson, 1 course + TP)