activity
20122021
most citedMean-Field Learning: a Survey

6 citations · 8 across the 10 of their papers we have counts for

collaborators
Showing math.NAShow all

8 papers · 1 filter

math.NA2021

Analysis of a class of Multi-Level Markov Chain Monte Carlo algorithms based on Independent Metropolis-Hastings

Juan Pablo Madrigal-Cianci, Fabio Nobile, Raul Tempone

In this work, we present, analyze, and implement a class of Multi-Level Markov chain Monte Carlo (ML-MCMC) algorithms based on independent Metropolis-Hastings proposals for Bayesia…

math.NA2020

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_…

math.NA20201 cited

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…

math.NA2020

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…

math.NA2019

Solution of the 3D density-driven groundwater flow problem with uncertain porosity and permeability

Alexander Litvinenko, Dmitry Logashenko, Raul Tempone +2

As groundwater is an essential nutrition and irrigation resource, its pollution may lead to catastrophic consequences. Therefore, accurate modeling of the pollution of the soil and…

math.NA2018

Multilevel Double Loop Monte Carlo and Stochastic Collocation Methods with Importance Sampling for Bayesian Optimal Experimental Design

Joakim Beck, Ben Mansour Dia, Luis F. R. Espath +1

An optimal experimental set-up maximizes the value of data for statistical inferences and predictions. The efficiency of strategies for finding optimal experimental set-ups is part…