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Provenance Data in the Machine Learning Lifecycle in Computational
  Science and Engineering

Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering

9 October 2019
Renan Souza
L. Azevedo
Vítor Lourenço
E. Soares
R. Thiago
R. Brandão
Daniel Salles Civitarese
E. V. Brazil
M. Moreno
P. Valduriez
M. Mattoso
Renato F. G. Cerqueira
M. Netto
    AI4TS
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Papers citing "Provenance Data in the Machine Learning Lifecycle in Computational Science and Engineering"

6 / 6 papers shown
Title
Optimization's Neglected Normative Commitments
Optimization's Neglected Normative Commitments
Benjamin Laufer
T. Gilbert
Helen Nissenbaum
OffRL
21
4
0
27 May 2023
Tracing and Visualizing Human-ML/AI Collaborative Processes through
  Artifacts of Data Work
Tracing and Visualizing Human-ML/AI Collaborative Processes through Artifacts of Data Work
Jennifer Rogers
Anamaria Crisan
16
7
0
05 Apr 2023
EdnaML: A Declarative API and Framework for Reproducible Deep Learning
EdnaML: A Declarative API and Framework for Reproducible Deep Learning
Abhijit Suprem
Sanjyot Vaidya
A. Venugopal
J. Ferreira
C. Pu
MoE
15
1
0
13 Nov 2022
Management of Machine Learning Lifecycle Artifacts: A Survey
Management of Machine Learning Lifecycle Artifacts: A Survey
Marius Schlegel
K. Sattler
17
35
0
21 Oct 2022
Preventing Machine Learning Poisoning Attacks Using Authentication and
  Provenance
Preventing Machine Learning Poisoning Attacks Using Authentication and Provenance
Jack W. Stokes
P. England
K. Kane
AAML
13
14
0
20 May 2021
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
AI4TS
AI4CE
21
31
0
30 Sep 2020
1