A.A. 2026-2027
Generative AI: Metodi e Applicazioni
PhD Course - Introduction to Deep Generative Models
Statistical and Mathematical Methods for Machine Learning
A.A. 2025-2026
PhD Course - Introduction to Deep Generative Models
Computational Imaging
- Basics of Neural Networks
- Basics of Pytorch
- End-to-End Neural Networks
- Generative Models
- Diffusion Models for Inverse Problems
Statistical and Mathematical Methods for Machine Learning
- Introduction to Python
- Basics of Machine Learning
- Gradient Descent (GD)
- Stochastic Gradient Descent (SGD)
- Supervised Learning
- Unsupervised Learning
A.A. 2024-2025
Computational Imaging
Calcolo Numerico
- Introduzione a Python
- Approssimazione di Dati mediante Minimi Quadrati
- Underfit/Overfit
- Introduzione all’Ottimizzazione Numerica
- Metodo di Discesa del Gradiente
- Metodo dei Gradienti Coniugati