19 citations · 25 across the 9 of their papers we have counts for
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physics.comp-ph2020
Enhanced data efficiency using deep neural networks and Gaussian processes for aerodynamic design optimization
S. Ashwin Renganathan, Romit Maulik and, Jai Ahuja
Adjoint-based optimization methods are attractive for aerodynamic shape design primarily due to their computational costs being independent of the dimensionality of the input space…
math.OC2020
Recursive Two-Step Lookahead Expected Payoff for Time-Dependent Bayesian Optimization
S. Ashwin Renganathan, Jeffrey Larson, Stefan Wild
We propose a novel Bayesian method to solve the maximization of a time-dependent expensive-to-evaluate oracle. We are interested in the decision that maximizes the oracle at a fini…