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20182026
most citedANODE: Unconditionally Accurate Memory-Efficient Gradients for Neural ODEs

79 citations · 95 across the 26 of their papers we have counts for

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9 papers · 1 filter

math.NA2026

A performance portable fast Ewald summation for Stokes flow

Gabriel Kosmacher, Ziyu Du, Joar Bagge +1

We present GPU algorithms for Ewald summation methods for accelerating N-body Stokes flow problems in periodic domains. Like most N-body codes, Ewald sums use a near-field/far-fiel…

math.NA2026

IV-Net: A neural network for elliptic PDEs with random and highly varying coefficients

Shan Zhong, George Biros

We introduce a novel neural operator architecture designed to approximate solutions of linear elliptic partial differential equations with high-contrast, spatially varying coeffici…

math.NA2024

Inverse Problem Regularization for 3D Multi-Species Tumor Growth Models

Ali Ghafouri, George Biros

We present a multi-species partial differential equation (PDE) model for tumor growth and a an algorithm for calibrating the model from magnetic resonance imaging (MRI) scans. The…

math.NA2023

An O(N) distributed-memory parallel direct solver for planar integral equations

Tianyu Liang, Chao Chen, Per-Gunnar Martinsson +1

Boundary value problems involving elliptic PDEs such as the Laplace and the Helmholtz equations are ubiquitous in mathematical physics and engineering. Many such problems can be al…

math.NA2023

Numerical simulation of an extensible capsule using regularized Stokes kernels and overset finite differences

Dhwanit Agarwal, George Biros

In this paper, we present a novel numerical scheme for simulating deformable and extensible capsules suspended in a Stokesian fluid. The main feature of our scheme is a partition-o…

math.NA2020

RCHOL: Randomized Cholesky Factorization for Solving SDD Linear Systems

Chao Chen, Tianyu Liang, George Biros

We introduce a randomized algorithm, namely RCHOL, to construct an approximate Cholesky factorization for a given Laplacian matrix (a.k.a., graph Laplacian). From a graph perspecti…