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Numerical Instabilities in Analytical Pipelines Lead to Large and Meaningful Variability in Brain Networks
View ORCID ProfileGregory Kiar, View ORCID ProfileYohan Chatelain, View ORCID ProfilePablo de Oliveira Castro, Eric Petit, View ORCID ProfileAriel Rokem, View ORCID ProfileGaël Varoquaux, View ORCID ProfileBratislav Misic, Alan C. Evans, View ORCID ProfileTristan Glatard
doi: https://doi.org/10.1101/2020.10.15.341495
Gregory Kiar
1Montréal Neurological Institute, McGill University, Montréal, QC, Canada
Yohan Chatelain
2Department of Computer Science and Software Engineering, Concordia University, Montréal, QC, Canada
Pablo de Oliveira Castro
3Department of Computer Science, Université of Versailles, Versailles, France
Eric Petit
4Exascale Computing Lab, Intel, Paris, France
Ariel Rokem
5Department of Psychology and eScience Institute, University of Washington, Seattle, WA, USA
Gaël Varoquaux
6Parietal project-team, INRIA Saclay-ile de France, France
Bratislav Misic
1Montréal Neurological Institute, McGill University, Montréal, QC, Canada
Alan C. Evans
1Montréal Neurological Institute, McGill University, Montréal, QC, Canada
Tristan Glatard
2Department of Computer Science and Software Engineering, Concordia University, Montréal, QC, Canada
Posted October 15, 2020.
Numerical Instabilities in Analytical Pipelines Lead to Large and Meaningful Variability in Brain Networks
Gregory Kiar, Yohan Chatelain, Pablo de Oliveira Castro, Eric Petit, Ariel Rokem, Gaël Varoquaux, Bratislav Misic, Alan C. Evans, Tristan Glatard
bioRxiv 2020.10.15.341495; doi: https://doi.org/10.1101/2020.10.15.341495
Numerical Instabilities in Analytical Pipelines Lead to Large and Meaningful Variability in Brain Networks
Gregory Kiar, Yohan Chatelain, Pablo de Oliveira Castro, Eric Petit, Ariel Rokem, Gaël Varoquaux, Bratislav Misic, Alan C. Evans, Tristan Glatard
bioRxiv 2020.10.15.341495; doi: https://doi.org/10.1101/2020.10.15.341495
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