Record link: 
http://hdl.handle.net/20.500.12708/153555
-
Title: 
Building Robust Machine Learning Force Fields by Composite Gaussian Approximation Potentials
en
Citation: 
Milardovich, D., Waldhoer, D., Jech, M., El-Sayed, A.-M. B., & Grasser, T. (2022). Building Robust Machine Learning Force Fields by Composite Gaussian Approximation Potentials. In SISPAD 2022: International Conference on Simulation of Semiconductor Processes and Devices - Conference Abstract Booklet (pp. 61–62). http://hdl.handle.net/20.500.12708/153555
-
Publication Type: 
Inproceedings - Full-Paper Contribution
en
Language: 
English
-
Authors: 
Milardovich, Diego 
Waldhoer, Dominic 
Jech, Markus 
El-Sayed, Al-Moatasem Bellah 
Grasser, Tibor 
-
Organisational Unit: 
E360 - Institut für Mikroelektronik 
-
Published in: 
SISPAD 2022: International Conference on Simulation of Semiconductor Processes and Devices - Conference Abstract Booklet 
-
Date (published): 
2022
-
Event name: 
2022 International Conference on Simulation of Semiconductor Processes and Devices (SISPAD 2022) 
-
Event date: 
6-Sep-2022 - 8-Sep-2022
-
Event place: 
Granada, Spain
-
Number of Pages: 
2
-
Peer reviewed: 
Yes
-
Keywords: 
Electrical and Electronic Engineering; Condensed Matter Physics; Electronic, Optical and Magnetic Materials; Materials Chemistry
-
Research Areas: 
Modelling and Simulation: 100%
-
Science Branch: 
Elektrotechnik, Elektronik, Informationstechnik
-
Appears in Collections:
Conference Paper

Show full item record

Items in reposiTUm are protected by copyright, with all rights reserved, unless otherwise indicated.

Page view(s)

36
checked on Oct 17, 2023

Google ScholarTM

Check