tag:joss.theoj.org,2005:/papers/tagged/learning%20analytics
Journal of Open Source Software
2023-06-16T16:37:49Z
Journal of Open Source Software
https://joss.theoj.org
tag:joss.theoj.org,2005:Paper/4218
2023-06-16T16:37:49Z
2023-06-17T09:15:49Z
Melissa: coordinating large-scale ensemble runs for deep learning and sensitivity analyses
accepted
V1.0.0
2023-02-17 13:28:46 UTC
86
2023-06-16 16:37:49 UTC
8
2023
5291
Marc
Schouler
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France
0000-0002-3708-4135
Robert
Alexander
Caulk
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France
0000-0001-5618-8629
Lucas
Meyer
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France, Industrial AI Laboratory SINCLAIR, EDF Lab Paris-Saclay, France
0000-0001-5386-5997
Théophile
Terraz
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France
Christoph
Conrads
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France
Sebastian
Friedemann
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France
Achal
Agarwal
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France
0000-0002-3216-4769
Juan
Manuel
Baldonado
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France
Bartłomiej
Pogodziński
Institute of Bioorganic Chemistry Polish Academy of Sciences, Poznań Supercomputing and Networking Center
Anna
Sekuła
Institute of Bioorganic Chemistry Polish Academy of Sciences, Poznań Supercomputing and Networking Center
0000-0003-3524-3160
Alejandro
Ribes
Industrial AI Laboratory SINCLAIR, EDF Lab Paris-Saclay, France
Bruno
Raffin
Univ. Grenoble Alpes, Inria, CNRS, Grenoble INP, LIG, France
10.21105/joss.05291
https://doi.org/10.5281/zenodo.8046630
C, Fortran, Python
https://joss.theoj.org/papers/10.21105/joss.05291.pdf
supercomputing, sensitivity analysis, deep learning, distributed systems, orchestration
tag:joss.theoj.org,2005:Paper/561
2018-08-08T12:09:33Z
2021-02-15T11:33:11Z
RISE: An R package for RISE analysis
accepted
v1.0
2018-07-20 17:47:46 UTC
28
2018-08-08 12:09:33 UTC
3
2018
846
David
Wiley
Lumen Learning, Brigham Young University
0000-0001-6722-4744
10.21105/joss.00846
https://doi.org/10.5281/zenodo.1340648
R
https://joss.theoj.org/papers/10.21105/joss.00846.pdf
learning analytics, open educational resources, continuous improvement