Edoardo Rossi

I'm an assistant professor at Roma Tre University. My research activities are focused on the characterization and modelling of nano-engineered materials, surfaces, and their interplayed role, along with environmental parameters, in determining materials performances.

Gaussian Process Regression — MecaNano Tutorial Series

This tutorial introduces Gaussian Process Regression (GPR), a non-parametric probabilistic approach widely adopted for interpolation, regression, and uncertainty quantification in materials science. The session explores both 1D and 2D inference, implemented with pyro.contrib.gp and PyTorch, with examples crafted for clarity and practical use.

Tutorial Slides

The following documents can be read directly from this page but are protected from downloading.

1. Overview of Gaussian Processes

2. Univariate GP Regression

3. Bivariate GP Regression

Note: Download buttons have been disabled for the embedded documents to protect the tutorial content. Please contact the authors for access.

Coming Soon: WG4 MecaNano Tutorial Series

 

We are excited to announce two upcoming video tutorials on Machine Learning & AI in materials science, delivered by WG4 leader Prof. Stefan Sandfeld.

  • Tutorial 1: Introduction to Machine Learning for Materials Scientists
    A beginner-friendly overview of machine learning techniques, using practical examples tailored to materials science.
  • Tutorial 2: From Specialist Models to Generalist Models in Materials AI
    Exploring the transition from specialized models to broad, generalist models in materials science AI.

The first tutorial will be released in November 2024. Stay tuned and enjoy our teaser video while we prepare the hands-on content.