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Toward Enabling Reproducibility for Data-Intensive Research using the
  Whole Tale Platform

Toward Enabling Reproducibility for Data-Intensive Research using the Whole Tale Platform

12 May 2020
Kyle Chard
N. Gaffney
M. Hategan
K. Kowalik
Bertram Ludäscher
T. McPhillips
J. Nabrzyski
V. Stodden
I. Taylor
Thomas Thelen
M. Turk
C. Willis
ArXiv (abs)PDFHTML

Papers citing "Toward Enabling Reproducibility for Data-Intensive Research using the Whole Tale Platform"

1 / 1 papers shown
Workflow Provenance in the Lifecycle of Scientific Machine Learning
Workflow Provenance in the Lifecycle of Scientific Machine Learning
Renan Souza
L. Azevedo
Vítor Lourencco
E. Soares
R. Thiago
...
M. Moreno
P. Valduriez
M. Mattoso
Renato F. G. Cerqueira
M. Netto
AI4TSAI4CE
311
42
0
30 Sep 2020
1
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