CORDIS Project
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This project investigates how neural networks can be made more reliable by leveraging existing knowledge of mathematical truths, such as partial differential equations. It aims to understand the advantages of compositional approximation over traditional methods, ultimately leading to the development of more accurate ma…
Neural networks have firmly established themselves as powerful tools in many scientific domains, e.g. for protein folding, recovering images of black holes, or solving Schrödinger equations.
Although empirically highly successful, neural network based methods very often lack the mathematical foundation to be able to guarantee the accuracy of the solution they produce.
While this lack of reliability constitutes a major issue for many applications, I believe that, for scientific machine learning i…
UNIVERSITAT WIEN
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