A continuation multilevel Monte Carlo algorithm

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Local modifications of a computational domain are often performed in order to simplify the meshing process and to reduce computational costs and memory requirements. However, removing geometrical features of a domain often introduces a non-negligible error ...

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An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

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A continuation multilevel Monte Carlo algorithm

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Deciphering the nature of cell state transitions in single cells using quantitative modeling of temporal dynamics

Performing and Detecting Backdoor Attacks on Face Recognition Algorithms

Stability: a search for structure

Gibbs sampling the posterior of neural networks

Generalization of Scaled Deep ResNets in the Mean-Field Regime

Adaptive projected variational quantum dynamics

Graph generative deep learning models with an application to circuit topologies

Nonparametric estimation for SDE with sparsely sampled paths: An FDA perspective

Analysis-aware defeaturing of complex geometries with Neumann features

A Shape Derivative Approach to Domain Simplification

An equilibrated flux a posteriori error estimator for defeaturing problems

An Unbiased Method of Measuring the Ratio of Two Data Sets