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The Bayesian approach to solving inverse problems strongly depends on the choice of a prior. Usually, a prior is constructed from expert knowledge or known physical constraints in a probabilistic fashion. A modern alternative to formulate such expert knowledge are generative models, a popular tool in machine learning to generate data whose properties closely resemble a given database by an...

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Scanning probe based spectroscopy using broadband infrared radiation emerged as a promising imaging technique at nanometer spatial resolution. However, the pixel-by-pixel data acquisition leads to prohibitive imaging times and enhanced radiation damage. To overcome this issue, a novel hyperspectral imaging scheme was developed in this project using Bayesian compressed sensing (BCS).

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Originally developed for fast global sensitivity analysis and efficient parameter reconstruction for applications in nano-optical metrology, PyThia provides an all purpose non-intrusive Python package to approximate high dimensional functions.
Based on general polynomial chaos approximation obtained via linear regression, PyThia generates functional surrogates by relying purely on training data...

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Es wurde ein neuartiger Ansatz basierend auf der Low-Rank-Matrixrekonstruktion eingeführt und in Verbindung mit Rasterkraftmikroskopie-basierender Infrarotspektroskopie (AFM-IR) angewandt, wodurch eine hocheffiziente hyperspektrale Infrarot-Nanobildgebung ermöglicht wird. Sein praktischer Nutzen wurde am Beispiel der Leishmania-Parasiten als eine realistische Probe von biologischer Bedeutung...

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Artificial intelligence is a powerful tool to assist physicians in diagnosing diseases. We extended this line of research by applying modern machine learning methods to the field of image quality assessment for mammography. Mammography is an established diagnostic technique to detect early forms of breast cancer. However, to ensure that a sufficient image quality can be obtained with a minimal...

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Statements of conformity are widespread to ensure that a measuring instrument conforms, e.g., to tolerance intervals. When linearly combining quantities, however, that are each measured with a conforming instrument according to ISO 17025, existing guidance to arrive at a conformity statement is often inapplicable or requires disproportionate efforts. Recent research identifies typical settings...

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Artificial intelligence and machine learning tools hold promise to assist or drive high-stakes decisions in areas such as finance, medicine, or autonomous driving. The upcoming AI Act will require that the principles by which such algorithms arrive at their predictions should be transparent. However, the field of XAI is lacking formal problem specifications and theoretical results. In a new study,...

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When a real measurement procedure is reproduced by simulations, it may be referred to as a “virtual measurement”. From a metrological point of view, the question is how to ensure confidence in such virtual measurements. While methods to estimate diverse sources of error in simulations have been developed over the past decades, there has to date been no accepted strategy for meeting the...

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Hydrogen plays an important role for the decarbonization of the energy sector. In its gaseous form, it is stored at pressures of up to 1000 bar at which real gas effects become relevant. To capture these effects in numerical simulations, accurate real gas models are required. We propose new correlation equations for relevant hydrogen properties …

 

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Uncertainty quantification can help to understand the behavior of a trained neural network and, in particular, foster confidence in its predictions. This is especially true for deep regression, where a single-point estimate of a sought function without any information regarding its accuracy can be largely meaningless. We propose a novel framework for benchmarking uncertainty quantification in deep...

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Bacteria organize in a variety of collective states, from swarming—rapid surface exploration, to biofilms—highly dense immobile communities attributed to stress resistance. It has been suggested that biofilm and swarming are oppositely controlled, making this transition  particularly  interesting  for  understanding  the  ability  of  bacterial  colonies to adapt to challenging environments....

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Image quality assessment is of particular relevance in image processing applications. This is especially true in mammography, where it helps to achieve a high detection quality at the lowest possible radiation dose. The assessment of image quality in mammography is carried out in accordance with the recommendation of a European Guideline. Recent research has shown that the use of deep neural...

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