CORDIS Project
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This fellowship aims to develop a nonlinear manifold learning framework for materials and process modeling. By integrating machine learning and advanced computational techniques, it seeks to enhance the understanding of material properties and processing methods.
The ambition of this fellowship, hosted by Professor S.P.A.
Bordas (UL), is to propose a nonlinear manifold learning framework, in particular to implement the Diffusion Maps methodology, enabled by “equation-free” calculations and Artificial Neural Networks, in the context of multi-scale materials and process modeling and design.
The goal is to push the boundaries of the “Digital Twins” paradigm beyond the current-state-of-the-art and to establish a methodological framework that links macro-scal…
UNIVERSITE DU LUXEMBOURG
Partner organizations (coordinator is shown above), with normalized type and CORDIS activity type. Guests see up to 4 partners.
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Guests see up to 5 EuroSciVoc fields.
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