Generative Artificial Intelligence (GenAI) is profoundly transforming the scientific and technological landscape, raising fundamental questions about the mathematical principles that underlie generative models, along with their potentialities and weaknesses. While deep learning architectures such as diffusion models, transformers, and variational autoencoders are achieving large success in generating complex data, a comprehensive understanding of their theoretical foundations remains an open and rapidly evolving field of inquiry.
The aim of the MathGen Summit is to bring together international researchers from different fields to foster a dialogue on the theoretical, algorithmic, and application-related aspects of GenAI techniques. The focus will be on the analysis and development of mathematical models and computational practices that explain, predict, or enhance generative behavior.
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