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Record link: 
http://hdl.handle.net/20.500.12708/153568
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Title: 
Modeling Advanced Magnetoresistive Memory: A Journey from Finite Element Methods to Machine Learning Approaches
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Citation: 
Sverdlov, V., Bendra, M., Fiorentini, S., Ender, J., Orio, R., Hadámek, T., Loch, W. J., Jørstad, N. P., & Selberherr, S. (2022). Modeling Advanced Magnetoresistive Memory: A Journey from Finite Element Methods to Machine Learning Approaches. In 2nd Global Webinar on Nanoscience & Nanotechnology. 2 nd Global Webinar on Nanoscience & Nanotechnology, online, Unknown. http://hdl.handle.net/20.500.12708/153568
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Publication Type: 
Inproceedings - Keynote Contribution
en
Authors: 
Sverdlov, Viktor 
Bendra, Mario 
Fiorentini, Simone 
Ender, Johannes 
Orio, Roberto 
Hadámek, Tomás 
Loch, Wilton Jaciel 
Jørstad, Nils Petter 
Selberherr, Siegfried 
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Organisational Unit: 
E360 - Institut für Mikroelektronik 
E360-01 - Forschungsbereich Mikroelektronik 
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Published in: 
2nd Global Webinar on Nanoscience & Nanotechnology 
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Date (published): 
2022
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Event name: 
2 nd Global Webinar on Nanoscience & Nanotechnology 
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Event date: 
14-Mar-2022 - 15-Mar-2022
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Event place: 
online, Unknown
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Number of Pages: 
1
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Research Areas: 
Modelling and Simulation: 100%
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Science Branch: 
Elektrotechnik, Elektronik, Informationstechnik
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Appears in Collections:
Conference Paper

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