Talk Summary
This workshop aims to bring together researchers in stochastic analysis, statistics and theoretical machine learning for an exchange of ideas at the forefront of the field. The workshop will coincide with the visit of Professor Gerard Ben Arous, a leading expert in stochastic analysis and high-dimensional statistics, whose insights into deep learning theory offer an exceptional opportunity for meaningful collaborations. The event will feature a series of presentations and discussions around the mathematical underpinnings of modern machine learning techniques, including topics such as:
- Theoretical analysis of deep learning architectures
- High-dimensional statistics and learning theory
- Diffusion models
- Connections between stochastic differential equations and neural networks
- Generalization properties of machine learning models
