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@ARTICLE{Rittig:981162,
author = {Rittig, Jan Gerald and Ritzert, Martin and Schweidtmann,
Artur M. and Winkler, Stefanie and Weber, Jana M. and
Morsch, Philipp and Heufer, Karl Alexander and Grohe, Martin
and Mitsos, Alexander and Dahmen, Manuel},
title = {{G}raph machine learning for design of high-octane fuels},
reportid = {RWTH-2024-02829},
pages = {12 Seiten},
year = {2023},
cin = {416710 / 415510 / 122910 / 080066 / 120000 / 080011},
ddc = {660},
cid = {$I:(DE-82)416710_20140620$ / $I:(DE-82)415510_20190928$ /
$I:(DE-82)122910_20140620$ / $I:(DE-82)080066_20181203$ /
$I:(DE-82)120000_20140620$ / $I:(DE-82)080011_20140620$},
pnm = {HDS LEE - Helmholtz School for Data Science in Life, Earth
and Energy (HDS LEE) (HDS-LEE-20190612) / DFG project
390919832 - EXC 2186: Das Fuel Science Center – Adaptive
Umwandlungssysteme für erneuerbare Energie- und
Kohlenstoffquellen (390919832) / GRK 2236 - UNRAVEL -
UNcertainty and Randomness in Algorithms, VErification, and
Logic (282652900) / Doktorandenprogramm
(PHD-PROGRAM-20170404)},
pid = {G:(DE-Juel1)HDS-LEE-20190612 / G:(GEPRIS)390919832 /
G:(GEPRIS)282652900 / G:(DE-HGF)PHD-PROGRAM-20170404},
typ = {PUB:(DE-HGF)25},
eprint = {2206.00619},
howpublished = {arXiv:2206.00619},
archivePrefix = {arXiv},
SLACcitation = {$\%\%CITATION$ = $arXiv:2206.00619;\%\%$},
doi = {10.48550/ARXIV.2206.00619},
url = {https://publications.rwth-aachen.de/record/981162},
}
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