Zobrazeno 1 - 10
of 135
pro vyhledávání: '"Gross, Dennis"'
Autor:
Gross, Dennis, Spieker, Helge
We introduce a method to verify stochastic reinforcement learning (RL) policies. This approach is compatible with any RL algorithm as long as the algorithm and its corresponding environment collectively adhere to the Markov property. In this setting,
Externí odkaz:
http://arxiv.org/abs/2403.18725
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. The me
Externí odkaz:
http://arxiv.org/abs/2403.18731
Deep Reinforcement Learning (RL) agents are susceptible to adversarial noise in their observations that can mislead their policies and decrease their performance. However, an adversary may be interested not only in decreasing the reward, but also in
Externí odkaz:
http://arxiv.org/abs/2212.05337
This paper presents COOL-MC, a tool that integrates state-of-the-art reinforcement learning (RL) and model checking. Specifically, the tool builds upon the OpenAI gym and the probabilistic model checker Storm. COOL-MC provides the following features:
Externí odkaz:
http://arxiv.org/abs/2209.07133
Autor:
Adhikari, Ajaya, Hollander, Richard den, Tolios, Ioannis, van Bekkum, Michael, Bal, Anneloes, Hendriks, Stijn, Kruithof, Maarten, Gross, Dennis, Jansen, Nils, Pérez, Guillermo, Buurman, Kit, Raaijmakers, Stephan
Detection of military assets on the ground can be performed by applying deep learning-based object detectors on drone surveillance footage. The traditional way of hiding military assets from sight is camouflage, for example by using camouflage nets.
Externí odkaz:
http://arxiv.org/abs/2008.13671
We give a formal verification procedure that decides whether a classifier ensemble is robust against arbitrary randomized attacks. Such attacks consist of a set of deterministic attacks and a distribution over this set. The robustness-checking proble
Externí odkaz:
http://arxiv.org/abs/2005.05587
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Roman, Barbara, Mastoor, Yusuf, Zhang, Yingfan, Gross, Dennis, Springer, Danielle, Liu, Chengyu, Glancy, Brian, Murphy, Elizabeth
Publikováno v:
Journal of Physiology; Jan2024, Vol. 602 Issue 1, p113-128, 16p
Publikováno v:
Journal of Commercial Biotechnology. Aug2021, Vol. 26 Issue 2, p13-19. 7p.
Publikováno v:
Journal of Commercial Biotechnology. Aug2021, Vol. 26 Issue 2, p3-12. 10p.