297 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- ETH ZurichCH15 papers
- Technical University of MunichDE3 papers
- Institute of GeophysicsRU2 papers
- Swiss Seismological ServiceCH2 papers
- Agence Nationale pour la Gestion des Déchets RadioactifsFR1 paper
- Centre National de la Recherche ScientifiqueFR1 paper
- China Earthquake AdministrationCN1 paper
- Earthquake Engineering Research InstituteUS1 paper
- Institut des Sciences de la TerreFR1 paper
- Laboratoire d'Acoustique de l'Université du MansFR1 paper
- Laboratoire de Physique et Modélisation des Milieux CondensésFR1 paper
- Seoul National UniversityKR1 paper
5 papers · 1 filter
Design Space Exploration and Explanation via Conditional Variational Autoencoders in Meta-model-based Conceptual Design of Pedestrian Bridges
Vera M. Balmer, Sophia V. Kuhn, Rafael Bischof +4
For conceptual design, engineers rely on conventional iterative (often manual) techniques. Emerging parametric models facilitate design space exploration based on quantifiable perf…
On off-line and on-line Bayesian filtering for uncertainty quantification of structural deterioration
Antonios Kamariotis, Luca Sardi, Iason Papaioannou +2
Data-informed predictive maintenance planning largely relies on stochastic deterioration models. Monitoring information can be utilized to update sequentially the knowledge on time…
A framework for quantifying the value of vibration-based structural health monitoring
Antonios Kamariotis, Eleni Chatzi, Daniel Straub
The difficulty in quantifying the benefit of Structural Health Monitoring (SHM) for decision support is one of the bottlenecks to an extensive adoption of SHM on real-world structu…
Sequential Bayesian Inference for Uncertain Nonlinear Dynamic Systems: A Tutorial
Konstantinos E. Tatsis, Vasilis K. Dertimanis, Eleni N. Chatzi
In this article, an overview of Bayesian methods for sequential simulation from posterior distributions of nonlinear and non-Gaussian dynamic systems is presented. The focus is mai…
Bayesian tomography with prior-knowledge-based parametrization and surrogate modeling
Giovanni Angelo Meles, Niklas Linde, Stefano Marelli
We present a Bayesian tomography framework operating with prior-knowledge-based parametrization that is accelerated by surrogate models. Standard high-fidelity forward solvers solv…