79 citations · 91 across the 12 of their papers we have counts for
3 papers · 1 filter
Small-noise approximation for Bayesian optimal experimental design with nuisance uncertainty
Arved Bartuska, Luis Espath, Raúl Tempone
Calculating the expected information gain in optimal Bayesian experimental design typically relies on nested Monte Carlo sampling. When the model also contains nuisance parameters,…
On the equivalence of different adaptive batch size selection strategies for stochastic gradient descent methods
Luis Espath, Sebastian Krumscheid, Raúl Tempone +1
In this study, we demonstrate that the norm test and inner product/orthogonality test presented in \cite{Bol18} are equivalent in terms of the convergence rates associated with Sto…
Statistical Learning for Fluid Flows: Sparse Fourier divergence-free approximations
Luis Espath, Dmitry Kabanov, Jonas Kiessling +1
We reconstruct the velocity field of incompressible flows given a finite set of measurements. For the spatial approximation, we introduce the Sparse Fourier divergence-free (SFdf)…