bonndata catalog
Thumbnail for Replication Data for: Fully discrete analysis of the Galerkin POD neural network approximation with application to 3D acoustic wave scattering

Replication Data for: Fully discrete analysis of the Galerkin POD neural network approximation with application to 3D acoustic wave scattering

Open this dataset in the live repository

Important usage condition: Use and redistribution are governed by GPLv3. Review and comply with the license before using the data.
Persistent identifier
doi:10.60507/FK2/OJUHWY
Published version
1.0
Publication date
2025-10-24
License
GPLv3

Description

Dataset and code to replicate data from Fully discrete analysis of the Galerkin POD neural network approximation with application to 3D acoustic wave scattering. 2025. Authors: J. Dölz, F. Henríquez Submitted to SIAM Journal on Scientific Computing Arxiv: https://arxiv.org/abs/2502.01859

Creators

Keywords

Neural network approximation, Reduced basis method, Wave scattering

Files

Before downloading: Use and redistribution are governed by GPLv3. Review and comply with the license before using the data.
FileTypeBytesChecksum
NN-training.pytext/x-python11791MD5 b85fba2962acc17c746fb6bcda3faa6c
KL.ipynbapplication/x-ipynb+json2523MD5 f9ee319b732de1b9182f7c08ab893de3
.empty_place_holderapplication/octet-stream0MD5 d41d8cd98f00b204e9800998ecf8427e
KL.hdfapplication/x-hdf13152MD5 0ad8896667f0ef8e6187ddfc8a6420b4
NN-MSE-convergence.ipynbapplication/x-ipynb+json5039MD5 5833022b7eab9a0ce60d9c05795eb830
runit.shapplication/x-shellscript372MD5 aee3305756c0a2d2d5af37102c7f16db
-1.empty_place_holderapplication/octet-stream0MD5 d41d8cd98f00b204e9800998ecf8427e
32ksamples_wave1.hdfapplication/x-hdf2895395920MD5 7a47728cd5c9b5bd4c11c22296de0709
32ksamples_wave4.hdfapplication/x-hdf2895395920MD5 bbae899d988bb76a45329738dc8e2173
NN-L2-convergence.ipynbapplication/x-ipynb+json5995MD5 867267d33849bb279b4c2a362794213b
POD-ranks.ipynbapplication/x-ipynb+json2961MD5 3a4d095c0af90b5eefd121b744665225
READMEtext/plain; charset=UTF-84046MD5 39e1c1491c96f98d8d719bcf15a01a77

Citation

Dölz, Jürgen; Henríquez, Fernando, 2025-10-24, Replication Data for: Fully discrete analysis of the Galerkin POD neural network approximation with application to 3D acoustic wave scattering, doi:10.60507/FK2/OJUHWY, V1.0

Additional Dataverse fields

Id512
Dataset Typedataset
Internal Version Number14
Latest Version Publishing StateRELEASED
Release Time2025-10-24T14:00:19Z
Create Time2025-10-23T12:06:22Z
Citation Date2025-10-24
File Access RequestTrue

Export metadata

Static metadata exports available for this published dataset version:

Complete Dataverse metadata

Citation Metadata

Title title
Replication Data for: Fully discrete analysis of the Galerkin POD neural network approximation with application to 3D acoustic wave scattering
Author author
  1. Author Name
    Dölz, Jürgen
    Author Affiliation
    University of Bonn
    Author Identifier Scheme
    ORCID
    Author Identifier
    Type Name
    authorIdentifier
    Multiple
    False
    Type Class
    primitive
    Value
    https://orcid.org/0000-0003-3322-1187
    Expandedvalue
    Person Name
    Dölz, Jürgen
    @id
    https://orcid.org/0000-0003-3322-1187
    Scheme
    ORCID
    @type
    https://schema.org/Person
  2. Author Name
    Henríquez, Fernando
    Author Affiliation
    TU Vienna
Dataset Contact datasetContact
  1. Dataset Contact Name
    Dölz, Jürgen
    Dataset Contact Affiliation
    University of Bonn
    Dataset Contact Email
    jdoelz@uni-bonn.de
Ds Description dsDescription
  1. Ds Description Value
    Dataset and code to replicate data from Fully discrete analysis of the Galerkin POD neural network approximation with application to 3D acoustic wave scattering. 2025. Authors: J. Dölz, F. Henríquez Submitted to SIAM Journal on Scientific Computing Arxiv: https://arxiv.org/abs/2502.01859
Subject subject
  1. Mathematical Sciences
Free Keyword freeKeyword
  1. Free Keyword Value
    Neural network approximation
  2. Free Keyword Value
    Reduced basis method
  3. Free Keyword Value
    Wave scattering
Depositor depositor
Dölz, Jürgen
Date Of Deposit dateOfDeposit
2025-10-23

Software Metadata (CodeMeta v2.0)

Programming Language programmingLanguage
  1. Python 3.9.2
Software Requirements Item softwareRequirementsItem
  1. Software Requirements
    HDF5 1.10.6
  2. Software Requirements
    numpy 2.0.2
  3. Software Requirements
    scipy 1.13.1
  4. Software Requirements
    torch 2.5.1
  5. Software Requirements
    h5py 3.12.1

Expected crawler behaviour

Use a stable, truthful User-Agent with product/version and a working contact URL. Across all IP addresses and HTTP connections used by one crawler identity, allow no more than 5 requests in flight and wait at least 20 seconds between request starts. Crawl URLs listed in the catalog sitemap, including file pages and download URLs when they are published, use conditional requests, honor Retry-After, and apply exponential backoff after errors.

The welcome page may link to the interactive repository for human navigation. Automated clients must not treat that human link as a catalog crawl target.

Read the live machine-readable crawler policy before and during a crawl. Stop crawling when it reports CPU or memory utilization at or above 80% and 80% respectively.