DOE CODE   /    Search Results   /    Concentric Spherical GNN for 3D Representation Learning

Concentric Spherical GNN for 3D Representation Learning

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/CSNN
https://doi.org/10.11578/dc.20221009.1

SAVE / SHARE



SNL Badge

Abstract

SAND2022-1325 O This codebase implements a new deep learning model for 3D representation learning. It includes experiments on open-source point cloud and 3D mesh datasets, namely ModelNet40 and ShapeNet. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
Developers:
Fox, James [1] ;  Rajamanickam, Sivasabkaran [2][3]
  1. Georgia Institute of Technology, Atlanta, GA (United States)
  2. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  3. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Release Date:
2022-04-01
Project Type:
Open Source, Publicly Available Repository
Software Type:
Scientific
Programming Languages:
Python
Licenses:
BSD 3-clause "New" or "Revised" License
Sponsoring Org.:
Code ID:
94509
Site Accession Number:
SCR #2734
Research Org.:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Country of Origin:
United States

RESOURCE

Publicly Accessible Repository
https://github.com/sandialabs/CSNN
https://doi.org/10.11578/dc.20221009.1

SAVE / SHARE



SNL Badge

Citation Formats

Fox, James, and Rajamanickam, Sivasabkaran. Concentric Spherical GNN for 3D Representation Learning. Computer Software. https://github.com/sandialabs/CSNN. USDOE. 01 Apr. 2022. Web. doi:10.11578/dc.20221009.1.
Fox, James, & Rajamanickam, Sivasabkaran. (2022, April 01). Concentric Spherical GNN for 3D Representation Learning. [Computer software]. https://github.com/sandialabs/CSNN. https://doi.org/10.11578/dc.20221009.1.
Fox, James, and Rajamanickam, Sivasabkaran. "Concentric Spherical GNN for 3D Representation Learning." Computer software. April 01, 2022. https://github.com/sandialabs/CSNN. https://doi.org/10.11578/dc.20221009.1.
@misc{ doecode_94509,
title = {Concentric Spherical GNN for 3D Representation Learning},
author = {Fox, James and Rajamanickam, Sivasabkaran},
abstractNote = {SAND2022-1325 O This codebase implements a new deep learning model for 3D representation learning. It includes experiments on open-source point cloud and 3D mesh datasets, namely ModelNet40 and ShapeNet. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.},
doi = {10.11578/dc.20221009.1},
url = {https://doi.org/10.11578/dc.20221009.1},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20221009.1}},
year = {2022},
month = {apr}
}