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Regularity and sparse approximation of the recursive first moment equations for the lognormal Darcy problem

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Publications associées à Regularity and sparse approximation of the recursive first moment equations for the lognormal Darcy problem | EPFL Graph Search

Localization errors of the stochastic heat equation

David Jean-Michel Candil

In this thesis, we study the stochastic heat equation (SHE) on bounded domains and on the whole Euclidean space

\R^d.

We confirm the intuition that as the bounded domain increases to the whole space, both solutions become arbitrarily close to one another ...

EPFL2022

Regularity and sparse approximation of the recursive first moment equations for the lognormal Darcy problem

Graph Chatbot

Chattez avec Graph Search

TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression

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Localization errors of the stochastic heat equation

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Localization errors of the stochastic heat equation

Understanding Deep Neural Function Approximation in Reinforcement Learning via ϵ-Greedy Exploration

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Convex optimization in sums of Banach spaces

Multiple ergodic averages along functions from a Hardy field: convergence, recurrence and combinatorial applications

Dictionary Learning for Two-Dimensional Kendall Shapes

Single and multiple recurrence along non-polynomial sequences

MATHICSE Technical Report : Regularity and sparse approximation of the recursive first moment equations for the lognormal Darcy problem