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04/12/2022
Assessment of sub-sampling schemes for compressive nano-FTIR imaging
Nano-FTIR imaging is a powerful scanning-based technique at nanometer sp...
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03/15/2022
Generative models and Bayesian inversion using Laplace approximation
The Bayesian approach to solving inverse problems relies on the choice o...
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05/27/2021
Deep Ensembles from a Bayesian Perspective
Deep ensembles can be seen as the current state-of-the-art for uncertain...
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05/19/2021
Errors-in-Variables for deep learning: rethinking aleatoric uncertainty
We present a Bayesian treatment for deep regression using an Errors-in-V...
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03/12/2021
Hypothesis-based acceptance sampling for modules F and F1 of the European Measuring Instruments Directive
Millions of measuring instruments are verified each year before being pl...
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03/01/2021
Uncertainty Quantification by Ensemble Learning for Computational Optical Form Measurements
Uncertainty quantification by ensemble learning is explored in terms of ...
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07/01/2020
Deep Neural Networks for Computational Optical Form Measurements
Deep neural networks have been successfully applied in many different fi...
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06/15/2020
Detecting unusual input to neural networks
Evaluating a neural network on an input that differs markedly from the t...
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09/12/2019
Inspecting adversarial examples using the Fisher information
Adversarial examples are slight perturbations that are designed to fool ...
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07/30/2019
