Explainable and trustworthy AI (2023/2024)

Explainable and trustworthy AI (2023/2024)

General Information

SSD: ING-INF/05

CFU: 6

Lecturer: Eliana Pastor

Teaching Staff: Elena Baralis, Gabriele Ciravegna, Salvatore Greco, Eleonora Poeta

Schedule

  • Monday, 8:30-10:00 – classroom 12I
  • Thursday, 8:30-10:00 – classroom 7D
  • Friday, 8:30-10:00 –  classroom 11I

Teaching material

  • Course introduction (slides)
  • Trustworthy AI: definition and motivations (slides)
  • Explainable AI: taxonomy (slides)
  • Pre-modeling explainability (slides)
  • In-modeling explainability (slides)*
  • Post-hoc model agnostic – global (slides)
  • Post-hoc model agnostic – local surrogate models (slides)
  • Post-hoc model agnostic – local – explaining by removing/perturbing (slides)
  • Post-hoc (model agnostic) – local – gradient-based explanation methods (slides)
  • Concept-based Explainable AI – part I (slides)
  • Concept-based Explainable AI – part II (slides)
  • Introduction to NLP (slides)*
  • Evaluation of explanations (slides)
  • Attention-based Explainability (slides)
  • Adversarial Attacks (slides)

Laboratory material

The material is also available in Github.

Project