no code implementations • 22 May 2024 • Hamidreza Eivazi, Mahyar Alikhani, Jendrik-Alexander Tröger, Stefan Wittek, Stefan Hartmann, Andreas Rausch
Translating these problems into numerical simulations and solving them using numerical schemes, e. g. the finite element method, is costly due to the demand of solving initial boundary-value problems at multiple scales.
1 code implementation • 27 Mar 2024 • Hamidreza Eivazi, Stefan Wittek, Andreas Rausch
Operator learning provides methods to approximate mappings between infinite-dimensional function spaces.
1 code implementation • 12 Jul 2023 • Fidae El Morer, Stefan Wittek, Andreas Rausch
This work proposes a methodology to assess their suitability to plan inspections considering three dimensions: accuracy metrics, ability to produce long-term degradation curves and explainability.
no code implementations • 17 Jun 2023 • Nour Habib, Yunsu Cho, Abhishek Buragohain, Andreas Rausch
So Machine learning (ML) based anomaly detection, a technique to identify data that does not belong to the training data could be used as a safety measuring indicator during the development and operational time of such AI-based components.
no code implementations • 24 Aug 2021 • Andreas Rausch, Azarmidokht Motamedi Sedeh, Meng Zhang
Thus, novelty detection - identifying data that differ in some respect from the data used for training - becomes a safety measure for system development and operation.