10 citations · 13 across the 6 of their papers we have counts for
7 papers
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)…
Wind Field Reconstruction with Adaptive Random Fourier Features
Jonas Kiessling, Emanuel Ström, Raúl Tempone
We investigate the use of spatial interpolation methods for reconstructing the horizontal near-surface wind field given a sparse set of measurements. In particular, random Fourier…
Smaller generalization error derived for a deep residual neural network compared to shallow networks
Aku Kammonen, Jonas Kiessling, Petr Plecháč +3
Estimates of the generalization error are proved for a residual neural network with random Fourier features layers $\bar z_{\ell+1}=\bar z_\ell + \mathrm{Re}\sum_{k=1}^K\bar b_…
Adaptive random Fourier features with Metropolis sampling
Aku Kammonen, Jonas Kiessling, Petr Plecháč +2
The supervised learning problem to determine a neural network approximation with one hidden layer is studied…
Error analysis in Fourier methods for option pricing
Fabián Crocce, Juho Häppölä, Jonas Kiessling +1
We provide a bound for the error committed when using a Fourier method to price European options when the underlying follows an exponential \levy dynamic. The price of the option i…
Properties of cellular classes of chain complexes
Jonas Kiessling
In this paper we prove certain properties of cellular and acyclic classes of chain complexes of modules over a commutative Noetherian ring. In particular we show that if X is finit…