Abstract
This project is an implementation of the Bayesian Multitask Learning (BayesMTL) from the paper
Hierarchical Sparse Bayesian Multitask Model with Scalable Inference for Microbiome Analysis.
- Developers:
-
Goncalves, Andre [1]
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Release Date:
- 2024-08-07
- Project Type:
- Open Source, Publicly Available Repository
- Software Type:
- Scientific
- Version:
- 1.0.0
- Licenses:
-
MIT License
- Sponsoring Org.:
-
USDOE National Nuclear Security Administration (NNSA)Primary Award/Contract Number:AC52-07NA27344
- Code ID:
- 160451
- Site Accession Number:
- LLNL-CODE-2002528
- Research Org.:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
- Country of Origin:
- United States
Citation Formats
Goncalves, Andre.
Hierarchical Sparse Bayesian Multitask Model with Scalable Inference.
Computer Software.
https://github.com/LLNL/BayesMTL.
USDOE National Nuclear Security Administration (NNSA).
07 Aug. 2024.
Web.
doi:10.11578/dc.20250812.3.
Goncalves, Andre.
(2024, August 07).
Hierarchical Sparse Bayesian Multitask Model with Scalable Inference.
[Computer software].
https://github.com/LLNL/BayesMTL.
https://doi.org/10.11578/dc.20250812.3.
Goncalves, Andre.
"Hierarchical Sparse Bayesian Multitask Model with Scalable Inference." Computer software.
August 07, 2024.
https://github.com/LLNL/BayesMTL.
https://doi.org/10.11578/dc.20250812.3.
@misc{
doecode_160451,
title = {Hierarchical Sparse Bayesian Multitask Model with Scalable Inference},
author = {Goncalves, Andre},
abstractNote = {This project is an implementation of the Bayesian Multitask Learning (BayesMTL) from the paper
Hierarchical Sparse Bayesian Multitask Model with Scalable Inference for Microbiome Analysis.},
doi = {10.11578/dc.20250812.3},
url = {https://doi.org/10.11578/dc.20250812.3},
howpublished = {[Computer Software] \url{https://doi.org/10.11578/dc.20250812.3}},
year = {2024},
month = {aug}
}