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1 Ergebnisse
1
Towards Learning Stochastic Population Models by Gradient D..:
, In:
Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation
,
Kreikemeyer, Justin Noah
;
Andelfinger, Philipp
;
Uhrmacher, Adelinde M.
- p. 88-92 , 2024
Link:
https://dl.acm.org/doi/10.1145/3615979.3656058
RT T1 <cTitle>Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation</cTitle>: T1 <Title>Towards Learning Stochastic Population Models by Gradient Descent</Title> UL https://suche.suub.uni-bremen.de/peid=acm-3656058&Exemplar=1&LAN=DE A1 Kreikemeyer, Justin Noah A1 Andelfinger, Philipp A1 Uhrmacher, Adelinde M. PB ACM YR 2024 K1 automatic model generation K1 differentiable simulation K1 discrete-event simulation K1 gradient descent K1 stochastic simulation algorithm K1 Computing methodologies K1 Modeling and simulation K1 Model development and analysis K1 Modeling methodologies K1 Simulation types and techniques K1 Discrete-event simulation K1 Machine learning SP 88 OP 92 LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3615979.3656058 DO https://dl.acm.org/doi/10.1145/3615979.3656058 SF ELIB - SuUB Bremen
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