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263-2400-00L 6 Credits MSC , WBZ D-ITET , D-INFK , D-MATH , D-GESS
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Reliable and Trustworthy Artificial Intelligence

Lecturers & Examiners: Prof. Dr. Martin Vechev
VVZ CR 4.0

Last Updated: 2026-02-05 15:48:26

Abstract

Creating reliable and explainable probabilistic models is a fundamental challenge to solving the artificial intelligence problem. This course covers some of the latest and most exciting advances that bring us closer to constructing such models.

Objective

The main objective of this course is to expose students to the latest and most exciting research in the area of explainable and interpretable artificial intelligence, a topic of fundamental and increasing importance. Upon completion of the course, the students should have mastered the underlying methods and be able to apply them to a variety of problems. To facilitate deeper understanding, an important part of the course will be a group hands-on programming project where students will build a system based on the learned material.

Content

This comprehensive course covers some of the latest and most important research advances (over the last 3 years) underlying the creation of safe, trustworthy, and reliable AI (more information here: https://www.sri.inf.ethz.ch/teaching/reliableai21 ): * Adversarial Attacks on Deep Learning (noise-based, geometry attacks, sound attacks, physical attacks, autonomous driving, out-of-distribution) * Defenses against attacks * Combining gradient-based optimization with logic for encoding background knowledge * Complete Certification of deep neural networks via automated reasoning (e.g., via numerical relaxations, mixed-integer solvers). * Probabilistic certification of deep neural networks * Training deep neural networks to be provably robust via automated reasoning * Fairness (different notions of fairness, certifiably fair representation learning) * Federated Learning (introduction, security considerations)

Resources

Learning Materials (Links)

General Information

Language
English
Levels
MSC , WBZ
Frequency
Yearly recurring

Examination

Type
session examination
Mode
written 120 minutes
Aids
Two A4-pages (i.e. one two-sided or two one-sided A4-sheets of paper), either handwritten or 11 point minimum font size.
30% of your grade is determined by mandatory project work and 70% is determined by a written exam.

Course Components

Type Title Time & Place Hours
lecture Reliable and Trustworthy Artificial Intelligence
Online event: Will primarily take place online. Reserved rooms will remain blocked on campus for students to follow the course from there.
  • Wed 14:15-16:00 (HG G 3)
2 h weekly
exercise Reliable and Trustworthy Artificial Intelligence
Exercise session will start in the second week of the semester. Online event: Will primarily take place online. Reserved rooms will remain blocked on campus for students to follow the course from there.
  • Mon 12:15-14:00 (CAB G 56)
  • Wed 12:15-14:00 (CAB G 51)
2 h weekly
independent project Reliable and Trustworthy Artificial Intelligence No time listed 1 h weekly

Offered In