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1 Ergebnisse
1
MOPINNs : an evolutionary multi-objective approach to ph..:
, In:
Proceedings of the Genetic and Evolutionary Computation Conference Companion
,
de Wolff, Taco
;
Lincopi, Hugo Carrillo
;
Martí, Luis
. - p. 228-231 , 2022
Link:
https://dl.acm.org/doi/10.1145/3520304.3529071
RT T1
Proceedings of the Genetic and Evolutionary Computation Conference Companion
: T1
MOPINNs : an evolutionary multi-objective approach to physics-informed neural networks
UL https://suche.suub.uni-bremen.de/peid=acm-3529071&Exemplar=1&LAN=DE A1 de Wolff, Taco A1 Lincopi, Hugo Carrillo A1 Martí, Luis A1 Sanchez-Pi, Nayat PB ACM YR 2022 K1 evolutionary algorithms K1 multi-objective optimization (MOO) K1 physics-informed neural networks (PINNs) K1 weighted PINNs K1 Computing methodologies K1 Machine learning K1 Machine learning approaches K1 Neural networks K1 Bio-inspired approaches K1 Genetic algorithms K1 Applied computing K1 Physical sciences and engineering K1 Earth and atmospheric sciences K1 Environmental sciences K1 Modeling and simulation K1 Model development and analysis K1 Modeling methodologies K1 Mathematics of computing K1 Mathematical analysis K1 Differential equations K1 Partial differential equations K1 Learning paradigms K1 Multi-task learning SP 228 OP 231 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3520304.3529071 DO https://dl.acm.org/doi/10.1145/3520304.3529071 SF ELIB - SuUB Bremen
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