no code implementations • 7 Aug 2023 • Christoffer Riis, Francisco N. Antunes, Tatjana Bolić, Gérald Gurtner, Andrew Cook, Carlos Lima Azevedo, Francisco Câmara Pereira
Lastly, we discuss two practical approaches for reducing the computational burden of the metamodelling further: we introduce a stopping criterion for active learning based on the inherent uncertainty of the metamodel, and we show how the simulations used for the metamodel can be reused across key performance indicators, thus decreasing the overall number of simulations needed.
no code implementations • 29 Mar 2023 • Mayte Cano, Andrés Perillo, Juan Antonio López, Faustino Tello, Javier Poveda, Francisco Câmara, Francisco Antunes, Christoffer Riis, Ian Crook, Abderrazak Tibichte, Sandrine Molton, David Mocholí, Ricardo Herranz, Gérald Gurtner, Tatjana Bolić, Andrew Cook, Jovana Kuljanin, Xavier Prats
This White Paper sets out to explain the value that metamodelling can bring to air traffic management (ATM) research.
no code implementations • 22 Mar 2023 • Andrew Cook, Andy Hammerlindl, Warwick Tucker
We define a family of $C^1$ functions which we call "nowhere coexpanding functions" that is closed under composition and includes all $C^3$ functions with non-positive Schwarzian derivative.
no code implementations • 29 Jul 2019 • Andrew Cook, Bappaditya Mandal, Donna Berry, Matthew Johnson
This paper has been withdrawn by the authors due to insufficient or definition error(s) in the ethics approval protocol.