G. Tsialiamanis | DeepAI

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Featured Co-authors

N. Dervilis
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E. Chatzi
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∙ 07/19/2023

Towards a population-informed approach to the definition of data-driven models for structural dynamics

Machine learning has affected the way in which many phenomena for variou...

0 G. Tsialiamanis, et al. ∙

∙ 02/15/2023

On the Detection and Quantification of Nonlinearity via Statistics of the Gradients of a Black-Box Model

Detection and identification of nonlinearity is a task of high importanc...

0 G. Tsialiamanis, et al. ∙

∙ 02/15/2023

A Meta-Learning Approach to Population-Based Modelling of Structures

A major problem of machine-learning approaches in structural dynamics is...

0 G. Tsialiamanis, et al. ∙

∙ 08/18/2022

On an Application of Generative Adversarial Networks on Remaining Lifetime Estimation

A major problem of structural health monitoring (SHM) has been the progn...

0 G. Tsialiamanis, et al. ∙

∙ 03/08/2022

On generative models as the basis for digital twins

A framework is proposed for generative models as a basis for digital twi...

0 G. Tsialiamanis, et al. ∙

∙ 03/03/2022

On partitioning of an SHM problem and parallels with transfer learning

In the current work, a problem-splitting approach and a scheme motivated...

0 G. Tsialiamanis, et al. ∙

∙ 03/03/2022

On an application of graph neural networks in population based SHM

Attempts have been made recently in the field of population-based struct...

0 G. Tsialiamanis, et al. ∙

∙ 03/03/2022

On generating parametrised structural data using conditional generative adversarial networks

A powerful approach, and one of the most common ones in structural healt...

0 G. Tsialiamanis, et al. ∙

∙ 03/02/2022

On the application of generative adversarial networks for nonlinear modal analysis

Linear modal analysis is a useful and effective tool for the design and ...

10 G. Tsialiamanis, et al. ∙

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