ls-net4parametricpdes

Pieces of code for the experiments described in the manuscript "A Least-Squares-Based Neural Network (LS-Net) for Solving Linear Parametric PDEs", available at https://arxiv.org/pdf/2410.15089.

https://github.com/mathmode/ls-net4parametricpdes

Science Score: 44.0%

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  • CITATION.cff file
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  • codemeta.json file
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  • .zenodo.json file
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    Low similarity (3.0%) to scientific vocabulary
Last synced: 10 months ago · JSON representation ·

Repository

Pieces of code for the experiments described in the manuscript "A Least-Squares-Based Neural Network (LS-Net) for Solving Linear Parametric PDEs", available at https://arxiv.org/pdf/2410.15089.

Basic Info
  • Host: GitHub
  • Owner: Mathmode
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 12.8 MB
Statistics
  • Stars: 1
  • Watchers: 2
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 2 years ago · Last pushed over 1 year ago
Metadata Files
Readme Citation

README.md

LS-Net for Parametric PDEs

To reproduce the numerical results of each model problem, go to the corresponding folder and follow these steps:

  1. Execute Main.py to run the code and train the network. The raw-format results are saved in Saved_models.
  2. Run plot.py to generate the final graphics.

Owner

  • Name: Mathmode
  • Login: Mathmode
  • Kind: organization
  • Location: Spain

Group on Applied Mathematical Modeling, Statistics, and Optimization

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: LS-Net4ParametricPDEs
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Shima
    family-names: Baharlouei
    affiliation: University of the Basque Country (UPV/EHU)
    orcid: 'https://orcid.org/0000-0003-2066-6523'
  - given-names: Carlos
    family-names: Uriarte
    affiliation: University of the Basque Country (UPV/EHU)
    orcid: 'https://orcid.org/0000-0002-0155-3091'

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