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Deep learning seminar

Class at Faculty of Mathematics and Physics |
NPFL117

Syllabus

Presentations of recent results in the deep learning field. The papers are presented by the participants, with the papers being announced in advance to allow purposeful discussion.

The paper topics can span any deep learning application (image processing, natural language processing, speech processing, reinforcement learning, deep generative models, etc.) depending on the interest of the participants.

Annotation

In recent years, deep neural networks have been used to solve complex machine-learning problems and have achieved significant state-of-the-art results in many areas. The whole field of deep learning has been developing rapidly, with new methods and techniques emerging steadily.

The goal of the seminar is to follow the newest advancements in the deep learning field. The course takes form of a reading group – each lecture a paper is presented by one of the students. The paper is announced in advance, hence all participants can read it beforehand and can take part in the discussion of the paper