Rima Alaifari: Katalogdaten im Herbstsemester 2020 |
| Name | Frau Prof. Dr. Rima Alaifari |
| Lehrgebiet | Angewandte Mathematik |
| Adresse | Seminar für Angewandte Mathematik ETH Zürich, HG G 59.2 Rämistrasse 101 8092 Zürich SWITZERLAND |
| Telefon | +41 44 632 32 00 |
| rima.alaifari@sam.math.ethz.ch | |
| URL | http://www.sam.math.ethz.ch/~rimaa |
| Departement | Mathematik |
| Beziehung | Assistenzprofessorin |
| Nummer | Titel | ECTS | Umfang | Dozierende | |
|---|---|---|---|---|---|
| 401-4660-70L | Robustness of Deep Neural Networks  Number of participants limited to 40 | 4 KP | 2S | R. Alaifari | |
| Kurzbeschreibung | While deep neural networks have been very successfully employed in classification problems, their stability properties remain still unclear. In particular, the presence of so-called adversarial examples has demonstrated that state-of-the-art networks are extremely vulnerable to small perturbations in the data. | ||||
| Lernziel | In this seminar, we will consider the state-of-the-art in adversarial attacks and defenses. | ||||
| Voraussetzungen / Besonderes | Participants should already be familiar with the principles of deep neural networks. The course will also include programming that will require knowledge in using either PyTorch or Tensorflow. | ||||
| 401-5650-00L | Zurich Colloquium in Applied and Computational Mathematics  | 0 KP | 1K | R. Abgrall, R. Alaifari, H. Ammari, R. Hiptmair, S. Mishra, S. Sauter, C. Schwab | |
| Kurzbeschreibung | Research colloquium | ||||
| Lernziel | |||||