Seminars

Artificial Intelligence (AI) is expected to have a transformative impact on the natural sciences by enhancing modeling capabilities and improving the prediction of natural phenomena across multiple spatial and temporal scales.

Abstract not available

*Abstract*

Angular information is applied across domains such as navigation, virtual and augmented reality, and robotics to tackle research problems related to directions and orientations. It can be encoded into polarization to reveal hidden content, and it can also be encoded into parallax to track an object with high accuracy.

The seminar “From Score to Sound: Music Production in the AI Era” will explore the evolution of AI-driven methods for automatic music generation, from the early use of Recurrent Neural Networks to the latest Foundational Models.

The empirical theory of vision suggests that what we see reflects statistical regularities learned through experience rather than direct representations of physical reality. Recent advances in machine learning, particularly in foundation models, have revealed intriguing parallels with human visual perception.

Recent claims about the superiority of deep-nets to model human vision are based on the reproduction of either (a) neural recordings from different brain layers or (b) high-level behaviors included in Brain-Score.

*Abstract*

Stay tuned!

*Bio*

Stay tuned!

Abstract not available

In both federated learning (FL) and large language model (LLMs) optimization, a central challenge is effective learning under constraints, ranging from data heterogeneity and personalization to limited communication and black-box access.