6 citations · 8 across the 10 of their papers we have counts for
4 papers · 1 filter
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_…
Quantifying Uncertainty with a Derivative Tracking SDE Model and Application to Wind Power Forecast Data
Renzo Caballero, Ahmed Kebaier, Marco Scavino +1
We develop a data-driven methodology based on parametric Itô's Stochastic Differential Equations (SDEs) to capture the real asymmetric dynamics of forecast errors. Our SDE framewor…
A Wasserstein Coupled Particle Filter for Multilevel Estimation
Marco Ballesio, Ajay Jasra, Erik von Schwerin +1
In this paper, we consider the filtering problem for partially observed diffusions, which are regularly observed at discrete times. We are concerned with the case when one must res…
Multilevel Ensemble Kalman Filtering based on a sample average of independent EnKF estimators
Håkon Hoel, Gaukhar Shaimerdenova, Raúl Tempone
We introduce a new multilevel ensemble Kalman filter method (MLEnKF) which consists of a hierarchy of independent samples of ensemble Kalman filters (EnKF). This new MLEnKF method…