Numerical modeling of the brain poromechanics by high-order discontinuous Galerkin methods

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The analysis of the acceleration behavior of gradient-based eigensolvers with preconditioning presents a substantial theoretical challenge. In this work, we present a novel framework for preconditioning on Riemannian manifolds and introduce a metric, the l ...

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Numerical modeling of the brain poromechanics by high-order discontinuous Galerkin methods

Chattez avec Graph Search

Riemannian acceleration with preconditioning for symmetric eigenvalue problems

S-R2D2: a spherical extension of the R2D2 deep neural network series paradigm for wide-field radio-interferometric imaging

Individually optimized dynamic parallel transmit pulses for 3D high‐resolution SPACE imaging at 7T

A matrix-free high-order solver for the numerical solution of cardiac electrophysiology

A stable loosely-coupled scheme for cardiac electro-fluid-structure interaction

Scattering from Time-Modulated Transmission-Line Loads: Theory and Experiments in Acoustics

Universal Solution Manifold Networks (USM-Nets): Non-Intrusive Mesh-Free Surrogate Models for Problems in Variable Domains

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Deterministic particle approximation of aggregation-diffusion equations on unbounded domains

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