teaching

classes, workshops, and teaching material

PhD in Smart Computing, Unversità di Firenze

Numerical resolution of Differential Equations for applications using Physics-Informed Neural Networks
4CFU (16hrs)
Winter 2024: Lecturer
  • Graduate-level introduction to PINNs. Syllabus.

    All interested students should contact me at my personal mail

    Summary:

    The goal of the course is to introduce the concept of Physics Informed Deep Neural Networks (PINN), discuss its implementation from scratch in PyTorch and using advanced ad-hoc developed open-source libraries such as nvidia-modulus for addressing real-world problems in various fields (engineering, physics, oil)

    Exam:

    Option a: Discussion of a research work on the topic, selected by the student and accepted by the instructor; it has to be presented orally with a presentation and with a Git repo offering the students implementation of the code.

    Option b: Resolution of a small research problem discussed jointly with the instructor; presented either orally with a brief presentation or a written essay, and a Git repo.

    Repository with notebooks and other utilities: pandora.infn.it (it is password protected; I'll give it during the course)
  • 0. Introductory Lecture (1h+1h): slides and code
    09:00-11:00, January, 11, 2024 (Tentative). Aula 005, Plesso Didattico Morgagni - viale Morgagni, 44-48, 50134 Firenze (FI).
  • 1. Intro to Differential Equations & their numerical solution (1h+1h): slides and code
    09:00-11:00, January, 12, 2024 (Tentative). Aula 117, Plesso Didattico Morgagni - viale Morgagni, 44-48, 50134 Firenze (FI).
  • 2.Introduction to Physics Informed Neural Networks - Part I forward problems (2h+1h): slides and example code exercise code (solution code )
    09:00-12:00, January, 18, 2024 (Tentative). Aula 005, Plesso Didattico Morgagni - viale Morgagni, 44-48, 50134 Firenze (FI).
  • 3. Introduction to Physics Informed Neural Networks - Part II inverse problems and parametric PINNs (2h+1h): slides and exercise data (exercise solution for Heat equation)
    09:00-12:00, January, 19, 2024 (Tentative). Aula 005, Plesso Didattico Morgagni - viale Morgagni, 44-48, 50134 Firenze (FI).
  • 4. PINN with nVidia modulus - Part I Introduction & custom PDE (2h+1h): slides and code repository
    09:00-12:00, January, 25, 2024 (Tentative). Aula 209, Plesso Didattico Morgagni - viale Morgagni, 44-48, 50134 Firenze (FI).
  • 5. PINN with nVidia modulus - Part II custom geometry & different NN architecture (2h+1h): slides and code repository
    09:00-12:00, January, 26, 2024 (Tentative). Aula 209, Plesso Didattico Morgagni - viale Morgagni, 44-48, 50134 Firenze (FI).
  • Link to enrollment form: Mirror 1 Mirror 2 (either one of the two is ok)

    Link to Baltig (INFN gitlab) repository: mirror 1

    Useful updated list of relevant papers:Neural PDE Solver

    Useful tutorial to install (old version) nVidia modulus on Colab (not mine): video and colab (colab mirror 2)

    Lectures will be streamed on Discord Invite link to discord server

Hackathons

ML-INFN Hackathons. Advanced Level
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ML-INFN Hackathons. Base Level
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