In this section

Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)

Filippone, M. and Engler, R. (2016) Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE). [Data Collection]

Datacite DOI: 10.5525/gla.researchdata.279

Related Enlighten Publications

Funding:
College / School: College of Science and Engineering > School of Computing Science
Date Deposited: 07 Mar 2016 09:54
Related resources:
URI: https://researchdata.gla.ac.uk/id/eprint/279

Available Files

Data

code_ulisse15.tar.gz
- code_ulisse15.tar.gz
Visible to:Anyone
File size:498kB
License:CC BY 4.0

Read me

README
- README
Visible to:Anyone
File size:822B
License:CC BY 4.0

Repository Staff Only: Update this record

Cite this record

Filippone, M. and Engler, R. (2016); Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE)

University of Glasgow

DOI: 10.5525/gla.researchdata.279

Retrieved: 2025-07-18

Altmetric
Download Statistics

Downloads

Downloads per month over past year