activity
20202026
most citedImplicit low-rank Riemannian schemes for the time integration of stiff partial differential equations

7 citations · 19 across the 12 of their papers we have counts for

collaborators

12 papers

cs.LG2026

Stiefel-AdamW: Geometry-Aware AdamW for Linear Factorization Blocks

Emanuele Zangrando, Marco Sutti, Francesco Tudisco

A pervasive structural pattern in modern deep learning is the linear factorization block: a submodule of the form in which two parameter matrices are multiplied directly,…

math.NA2026

Low-rank solutions to a class of parametrized systems using Riemannian optimization

Marco Sutti, Tommaso Vanzan

We propose a computational framework for computing low-rank approximations to the ensemble of solutions of a parametrized system of the form for multiple pa…

math.NA2025

Toroidal area-preserving parameterizations of genus-one closed surfaces

Marco Sutti, Mei-Heng Yueh

We consider the problem of computing toroidal area-preserving parameterizations of genus-one closed surfaces. We propose four algorithms based on Riemannian geometry: the projected…

math.NA2024

Nonlinear Schwarz methods to compute geodesics on manifolds

Marco Sutti, Tommaso Vanzan

We consider the leapfrog algorithm by Noakes for computing geodesics on Riemannian manifolds. The main idea behind this algorithm is to subdivide the original endpoint geodesic pro…

math.NA2024★ 2 cited

A single shooting method with approximate Fréchet derivative for computing geodesics on the Stiefel manifold

Marco Sutti

This paper shows how to use the shooting method, a classical numerical algorithm for solving boundary value problems, to compute the Riemannian distance on the Stiefel manifold $ \…

math.NA2024★ 2 cited

Riemannian gradient descent for spherical area-preserving mappings

Marco Sutti, Mei-Heng Yueh

We propose a new Riemannian gradient descent method for computing spherical area-preserving mappings of topological spheres using a Riemannian retraction-based framework with theor…

math.NA2023★ 1 cited

Perfectly matched layers for the Boltzmann equation: stability and sensitivity analysis

Marco Sutti, Jan S. Hesthaven

We study the stability and sensitivity of an absorbing layer for the Boltzmann equation by examining the Bhatnagar-Gross-Krook (BGK) approximation and using the perfectly matched l…

math.NA2023

Shooting methods for computing geodesics on the Stiefel manifold

Marco Sutti

This paper shows how to use the shooting method, a classical numerical algorithm for solving boundary value problems, to compute the Riemannian distance on the Stiefel manifold $\m…

math.NA2023★ 7 cited

Implicit low-rank Riemannian schemes for the time integration of stiff partial differential equations

Marco Sutti, Bart Vandereycken

We propose two implicit numerical schemes for the low-rank time integration of stiff nonlinear partial differential equations. Our approach uses the preconditioned Riemannian trust…

physics.flu-dyn2022★ 1 cited

SPHM: a MATLAB package for Smoothed Particle Hydrodynamics simulations

Marco Sutti

We present a MATLAB code that implements the Smoothed Particle Hydrodynamics (SPH) method. The paper reviews the continuous Navier-Stokes equations as well as their SPH approximati…

math.NA2020★ 1 cited

The leapfrog algorithm as nonlinear Gauss-Seidel

Marco Sutti, Bart Vandereycken

Several applications in optimization, image, and signal processing deal with data that belong to the Stiefel manifold St(n,p), that is, the set of n-by-p matrices with orthonormal…

math.NA2020★ 5 cited

Riemannian multigrid line search for low-rank problems

Marco Sutti, Bart Vandereycken

Large-scale optimization problems arising from the discretization of problems involving PDEs sometimes admit solutions that can be well approximated by low-rank matrices. In this p…