CORDIS Project
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This project aims to develop a comprehensive mathematical theory for neural networks in control applications. By addressing current theoretical gaps, it seeks to enhance the safety, robustness, and reliability of neural networks in critical fields such as healthcare and aerospace.
As neural networks are delivering groundbreaking performance in various machine learning frameworks --- ranging from the basic framework of supervised learning to the powerful and challenging framework of control --- immense efforts focus on developing underlying mathematical theories.
Recent years witnessed breakthrough contributions to the theory of neural networks for supervised learning, by myself and others.
Yet, from a theoretical perspective, much is left to be elucidated about neural n…
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