Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Andre Eberhard"'
Autor:
Patrick Reiser, Marlen Neubert, André Eberhard, Luca Torresi, Chen Zhou, Chen Shao, Houssam Metni, Clint van Hoesel, Henrik Schopmans, Timo Sommer, Pascal Friederich
Publikováno v:
Communications Materials, Vol 3, Iss 1, Pp 1-18 (2022)
Graph neural networks are machine learning models that directly access the structural representation of molecules and materials. This Review discusses state-of-the-art architectures and applications of graph neural networks in materials science and c
Externí odkaz:
https://doaj.org/article/26a8ac8ff79b4428871a0977411be761
Publikováno v:
Machine Learning: Science and Technology, Vol 5, Iss 1, p 015055 (2024)
Transfer of recent advances in deep reinforcement learning to real-world applications is hindered by high data demands and thus low efficiency and scalability. Through independent improvements of components such as replay buffers or more stable learn
Externí odkaz:
https://doaj.org/article/9f7644dca12a4349b7076664469a0e7f
Autor:
Hassan Yassine, Christian Weber, Andre Eberhardt, Mahmoud El-Safoury, Jürgen Wöllenstein, Katrin Schmitt
Publikováno v:
Sensors, Vol 24, Iss 1, p 191 (2023)
The wide use of sulfuryl difluoride (SO2F2) for termite control in buildings, warehouses and shipping containers requires the implementation of suitable sensors for reliable detection. SO2F2 is highly toxic to humans and the environment, and moreover
Externí odkaz:
https://doaj.org/article/f3655fbffc97441180b5a1154e5913d5
Autor:
Pierre-Yves Carry, Yves Francois, Jean-Pierre Perdrix, Annie Sayag, Francois Gilly, Andre Eberhard, Vincent Banssillon, Pierre Baconnier
Publikováno v:
Anesthesia & Analgesia. 87:1393-1397
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f37631828757ae736e3ec9e7fd178e3d
https://doi.org/10.1213/00000539-199812000-00035
https://doi.org/10.1213/00000539-199812000-00035