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pro vyhledávání: '"A. Boetius"'
Probabilistic verification of neural networks is concerned with formally analysing the output distribution of a neural network under a probability distribution of the inputs. Examples of probabilistic verification include verifying the demographic pa
Externí odkaz:
http://arxiv.org/abs/2405.17556
Autor:
Boetius, David, Leue, Stefan
Naively trained Deep Reinforcement Learning agents may fail to satisfy vital safety constraints. To avoid costly retraining, we may desire to repair a previously trained reinforcement learning agent to obviate unsafe behaviour. We devise a counterexa
Externí odkaz:
http://arxiv.org/abs/2405.15430
Autor:
Boetius, David, Leue, Stefan
Current approaches to neural network verification focus on specifications that target small regions around known input data points, such as local robustness. Thus, using these approaches, we can not obtain guarantees for inputs that are not close to
Externí odkaz:
http://arxiv.org/abs/2306.12495
Counterexample-guided repair aims at creating neural networks with mathematical safety guarantees, facilitating the application of neural networks in safety-critical domains. However, whether counterexample-guided repair is guaranteed to terminate re
Externí odkaz:
http://arxiv.org/abs/2301.11342
Autor:
Albers, Elmar, Behrendt, Nele, Diehl, Alexander, Genske, Felix, Monien, Patrick, Kasemann, Simone A., Purser, Autun, Boetius, Antje, Bach, Wolfgang
Publikováno v:
In Marine Geology September 2024 475
Autor:
Ramirez-Llodra, Eva, Argentino, Claudio, Baker, Maria, Boetius, Antje, Costa, Carolina, Dahle, Håkon, Denny, Emily M., Dessandier, Pierre-Antoine, Eilertsen, Mari H., Ferre, Benedicte, German, Christopher R., Hand, Kevin, Hilário, Ana, Hislop, Lawrence, Jamieson, John W., Kalnitchenko, Dimitri, Mall, Achim, Panieri, Giuliana, Purser, Autun, Ramalho, Sofia P., Reeves, Eoghan P., Rolley, Leighton, Pereira, Samuel I., Ribeiro, Pedro A., Sert, Muhammed Fatih, Steen, Ida H., Stetzler, Marie, Stokke, Runar, Victorero, Lissette, Vulcano, Francesca, Vågenes, Stig, Waghorn, Kate Alyse, Buenz, Stefan
Publikováno v:
Oceanography, 2023 Mar 01. 36(1), 6-17.
Externí odkaz:
https://www.jstor.org/stable/27200033
Publikováno v:
SPIN 2022
Deep neural networks (DNNs) are increasingly applied in safety-critical domains, such as self-driving cars, unmanned aircraft, and medical diagnosis. It is of fundamental importance to certify the safety of these DNNs, i.e. that they comply with a fo
Externí odkaz:
http://arxiv.org/abs/2106.01917
Akademický článek
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Autor:
Magda G. Cardozo-Mino, Ian Salter, Eva-Maria Nöthig, Katja Metfies, Simon Ramondenc, Claudia Wekerle, Thomas Krumpen, Antje Boetius, Christina Bienhold
Publikováno v:
Frontiers in Marine Science, Vol 10 (2023)
Marine sinking particles sequester atmospheric carbon dioxide to the deep ocean via the biological carbon pump. Understanding how environmental shifts drive changes in the microbial composition of particles, and how these affect the export of organic
Externí odkaz:
https://doaj.org/article/2b53f2d1dd574df49c649df0767759f3
Autor:
Henk-Jan Hoving, Antje Boetius, Katherine Dunlop, Jens Greinert, Matthias Haeckel, Daniel O. B. Jones, Erik Simon-Lledó, Yann Marcon, Tanja Stratmann, Inken Suck, Andrew K. Sweetman, Autun Purser
Publikováno v:
Frontiers in Marine Science, Vol 10 (2023)
Abyssal plain communities rely on the overlying water column for a settling flux of organic matter. The origin and rate of this flux as well as the controls on its fine-scale spatial distribution following seafloor settlement are largely unquantified
Externí odkaz:
https://doaj.org/article/3d5230af52734270b18fa65ca49de177