no code implementations • 27 Mar 2024 • Dennis Gross, Helge Spieker, Arnaud Gotlieb, Ricardo Knoblauch
This research presents a method that utilizes explainability techniques to amplify the performance of machine learning (ML) models in forecasting the quality of milling processes, as demonstrated in this paper through a manufacturing use case.
no code implementations • 27 Mar 2024 • Dennis Gross, Helge Spieker
We introduce a method to verify stochastic reinforcement learning (RL) policies.
2 code implementations • 10 Dec 2022 • Dennis Gross, Thiago D. Simao, Nils Jansen, Guillermo A. Perez
We use this metric to craft optimal adversarial attacks.
3 code implementations • 15 Sep 2022 • Dennis Gross, Nils Jansen, Sebastian Junges, Guillermo A. Perez
This paper presents COOL-MC, a tool that integrates state-of-the-art reinforcement learning (RL) and model checking.
no code implementations • 31 Aug 2020 • Ajaya Adhikari, Richard den Hollander, Ioannis Tolios, Michael van Bekkum, Anneloes Bal, Stijn Hendriks, Maarten Kruithof, Dennis Gross, Nils Jansen, Guillermo Pérez, Kit Buurman, Stephan Raaijmakers
The traditional way of hiding military assets from sight is camouflage, for example by using camouflage nets.
no code implementations • 12 May 2020 • Dennis Gross, Nils Jansen, Guillermo A. Pérez, Stephan Raaijmakers
The robustness-checking problem consists of assessing, given a set of classifiers and a labelled data set, whether there exists a randomized attack that induces a certain expected loss against all classifiers.