Copertina

PETScML: Second-order solvers for training regression problems in Scientific Machine Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zampini, Stefano, Zerbinati, Umberto, Turkiyyah, George, Keyes, David
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning Mathematical Software Optimization and Control 65K10, 68T07, 65M70, 65Y05 I.2.5; D.2.m; G.4; G.1.6; J.2
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Learning Nonlinear Finite Element Solution Operators using Multilayer Perceptrons and Energy Minimization
di: Larson, Mats G., et al.
Pubblicazione: (2024)

Fast GPU Linear Algebra via Compile Time Expression Fusion
di: Curtin, Ryan R., et al.
Pubblicazione: (2026)

Armadillo: An Efficient Framework for Numerical Linear Algebra
di: Sanderson, Conrad, et al.
Pubblicazione: (2025)

Recent advances about the rigorous integration of parabolic PDEs via fully spectral Fourier-Chebyshev expansions
di: Cadiot, Matthieu, et al.
Pubblicazione: (2025)

Hardware Trends Impacting Floating-Point Computations In Scientific Applications
di: Dongarra, Jack, et al.
Pubblicazione: (2024)

Implementation techniques for multigrid solvers for high-order Discontinuous Galerkin methods
di: Baccas, Sean, et al.
Pubblicazione: (2025)

Learn and Verify: A Framework for Rigorous Verification of Physics-Informed Neural Networks
di: Tanaka, Kazuaki, et al.
Pubblicazione: (2026)

Beating Posits at Their Own Game: Takum Arithmetic
di: Hunhold, Laslo
Pubblicazione: (2024)

IGA-ODIL: Optimizing DIscretre robust Loss with Isogeometric Analysis to solve forward and inverse problems faster using machine learning tools
di: Paszyński, Maciej, et al.
Pubblicazione: (2026)

Mixed Precision FGMRES-Based Iterative Refinement for Weighted Least Squares
di: Carson, Erin, et al.
Pubblicazione: (2024)

Hybrid metapopulation agent-based epidemiological models for efficient insight on the individual scale: a contribution to green computing
di: Bicker, Julia, et al.
Pubblicazione: (2024)

Scalable s-step Preconditioned Conjugate Gradient with Chebyshev Basis and Gauss-Seidel Gram Solve
di: D'Ambra, Pasqua, et al.
Pubblicazione: (2026)

Challenges in automatic differentiation and numerical integration in physics-informed neural networks modelling
di: Daněk, Josef, et al.
Pubblicazione: (2024)

Deceptron: Learned Local Inverses for Fast and Stable Physics Inversion
di: Kachhadiya, Aaditya L.
Pubblicazione: (2025)

Inexact Gauss Seidel and Coarse Solvers for AMG and s-step CG
di: Thomas, Stephen, et al.
Pubblicazione: (2025)

RANDSMAPs: Random-Feature/multi-Scale Neural Decoders with Mass Preservation
di: Patsatzis, Dimitrios G., et al.
Pubblicazione: (2026)

Small errors in random zeroth-order optimization are imaginary
di: Jongeneel, Wouter, et al.
Pubblicazione: (2021)

Robust and scalable nonlinear solvers for finite element discretizations of biological transportation networks
di: Haskovec, Jan, et al.
Pubblicazione: (2025)

Mixed precision thin SVD algorithms based on the Gram matrix
di: Carson, Erin, et al.
Pubblicazione: (2026)

Multigrid with Linear Storage Complexity
di: Bauer, Daniel, et al.
Pubblicazione: (2025)

Python library supporting Discrete Variational Formulations and training solutions with Collocation-based Robust Variational Physics Informed Neural Networks (DVF-CRVPINN)
di: Służalec, Tomasz, et al.
Pubblicazione: (2026)

Systematic construction of continuous-time neural networks for linear dynamical systems
di: Datar, Chinmay, et al.
Pubblicazione: (2024)

MIRGE: An Array-Based Computational Framework for Scientific Computing
di: Diener, Matthias, et al.
Pubblicazione: (2025)

Fast Gaussian process inference by exact Matérn kernel decomposition
di: Langrené, Nicolas, et al.
Pubblicazione: (2025)

Genetic AI: Evolutionary Games for ab initio dynamic Multi-Objective Optimization
di: Wissgott, Philipp
Pubblicazione: (2025)

A Method of Fundamental Solutions for Large-Scale 3D Elastance and Mobility Problems
di: Broms, Anna, et al.
Pubblicazione: (2024)

Data-Driven Stochastic Optimal Control for Intraday Electricity Trading by Renewable Producers
di: Hammouda, Chiheb Ben, et al.
Pubblicazione: (2026)

Mixed Precision Training of Neural ODEs
di: Celledoni, Elena, et al.
Pubblicazione: (2025)

Non-convergence to the optimal risk for Adam and stochastic gradient descent optimization in the training of deep neural networks
di: Do, Thang, et al.
Pubblicazione: (2025)

Reorthogonalized Pythagorean variants of block classical Gram-Schmidt
di: Carson, Erin, et al.
Pubblicazione: (2024)

On the loss of orthogonality in low-synchronization variants of reorthogonalized block classical Gram-Schmidt
di: Carson, Erin, et al.
Pubblicazione: (2024)

Do Inner Greenland's Melt Rate Dynamics Approach Coastal Ones?
di: Heßler, Martin, et al.
Pubblicazione: (2024)

The need for accuracy and smoothness in numerical simulations
di: Mikkelsen, Carl Christian Kjelgaard, et al.
Pubblicazione: (2024)

Trilinos: Enabling Scientific Computing Across Diverse Hardware Architectures at Scale
di: Mayr, Matthias, et al.
Pubblicazione: (2025)

NumCalc: An open source BEM code for solving acoustic scattering problems
di: Kreuzer, Wolfgang, et al.
Pubblicazione: (2023)

Evolutionary Data Theory: On the Similarities between Data Problems and Evolutionary Games
di: Wissgott, Philipp
Pubblicazione: (2026)

Collocation-based Robust Variational Physics-Informed Neural Networks (CRVPINN)
di: Łoś, Marcin, et al.
Pubblicazione: (2024)

A tensor-train reduced basis solver for parameterized partial differential equations on Cartesian grids
di: Mueller, Nicholas, et al.
Pubblicazione: (2024)

Space-time parallel iterative solvers for the integration of parabolic problems
di: Arrarás, Andrés, et al.
Pubblicazione: (2025)

A stable one-synchronization variant of reorthogonalized block classical Gram--Schmidt
di: Carson, Erin, et al.
Pubblicazione: (2024)