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15.08.2022 20:50:57
Practical training: 2.01.494 Applied Verification Lab: Neural Networks - Details
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General information

Course name Practical training: 2.01.494 Applied Verification Lab: Neural Networks
Subtitle inf494
Course number 2.01.494
Semester Sommersemester 2022
Current number of participants 11
expected number of participants 12
Home institute Department of Computing Science
Courses type Practical training in category Teaching
First date Wed., 20.04.2022 12:15 - 13:45, Room: A03 2-209
Type/Form 2P
Participants The intended audience is computer science or math students with background in algorithms, logic, and deep neural networks.
Pre-requisites We assume familiarity with algorithms and logic. In-depth familiarity with deep learning is not required, but you should know how to train neural networks. Basic Python skills are required. Please contact the instructor should you be unsure if you have the necessary background.
Lehrsprache englisch

Course location / Course dates

A03 2-209 Wed.. 12:15 - 13:45 (14x)


The exceptional performance of deep neural networks in areas such as perception and natural language processing has made them an integral part of many real-world AI systems, including safety-critical ones such as medical diagnosis and autonomous driving. However, neural networks are inherently opaque, and numerous defects have been found in state-of-the-art networks.

In this lab, we will apply various methods for proving the reliability of deep neural networks. In particular, we will use state-of-the-art tools, such as Crown, ERAN, Marabou, and Planet, and apply them to examples from the neural network verification competition.