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ORCIDEnrique G. Paredes
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Journal Articles
- 2019
[j2]Rafael Ballester-Ripoll
, Enrique G. Paredes, Renato Pajarola:
Sobol tensor trains for global sensitivity analysis. Reliab. Eng. Syst. Saf. 183: 311-322 (2019)- 2018
- [j1]Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola:
Tensor Algorithms for Advanced Sensitivity Metrics. SIAM/ASA J. Uncertain. Quantification 6(3): 1172-1197 (2018)
Conference and Workshop Papers
- 2019
- [c3]Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola:
Tensor Methods for Global Sensitivity Analysis. GI-Jahrestagung 2019: 275-276 - 2016
- [c2]David Steiner, Enrique G. Paredes, Stefan Eilemann, Renato Pajarola:
Dynamic Work Packages in Parallel Rendering. EGPGV@EuroVis 2016: 89-98 - [c1]Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola:
A surrogate visualization model using the tensor train format. SIGGRAPH Asia Symposium on Visualization 2016: 13:1-13:8
Data and Artifacts
- 2018
- [d1]Enrique G. Paredes, Rafael Ballester-Ripoll:
SGEMM GPU kernel performance. UCI Machine Learning Repository, 2018
Informal and Other Publications
- 2023
- [i3]Enrique G. Paredes, Linus Groner, Stefano Ubbiali, Hannes Vogt, Alberto Madonna, Kean Mariotti, Felipe A. Cruz, Lucas Benedicic, Mauro Bianco, Joost VandeVondele, Thomas C. Schulthess:
GT4Py: High Performance Stencils for Weather and Climate Applications using Python. CoRR abs/2311.08322 (2023) - 2017
- [i2]Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola:
Sobol Tensor Trains for Global Sensitivity Analysis. CoRR abs/1712.00233 (2017) - [i1]Rafael Ballester-Ripoll, Enrique G. Paredes, Renato Pajarola:
Tensor Approximation of Advanced Metrics for Sensitivity Analysis. CoRR abs/1712.01633 (2017)
Coauthor Index
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