Crash Lecture Series. Semester of Spring 2021
This lecture series is a preview of the full course of 16 hours starting in Autumn 2021.
Crash course Overview:
The “where and why” of interpretability. Reading of taxonomy papers and perspectives.
The “three dimensions” of interpretability. Activation maximizations, LIME surrogates, Class Activation maps and Concept Attribution methods seen in details with hands-on exercises.
Evaluation of interpretability methods. Reading of papers and hands-on exercises.
Prerequisites:
Confidence in linear algebra, probability, machine learning. Experience with Python, numpy, tensorflow.
Course registration: email mara dot graziani at hevs dot ch
Lecture 1: The Where and Why of Interpretability
Prof. Henning Müller and Mara Graziani (PhD student), Hes-so Valais and University of Geneva
May 20, Microsoft Teams
Lect 2: From attention models and saliency maps to the explainability of Deep Neural Networks.
Prof. Jenny Benois-Pineau, University of Bordeaux
May 27, Microsoft Teams
Lect. 3: The three dimensions of interpretability. Activation Maximization and Feature Attribution
May 28, Microsoft Teams
Lect. 4:
June 4, Microsoft Teams
