Keyword search (4,163 papers available)

"Kiar G" Authored Publications:

Title Authors PubMed ID
1 Numerical stability of DeepGOPlus inference Gonzalez Pepe I; Chatelain Y; Kiar G; Glatard T; 38285635
ENCS
2 Data and Tools Integration in the Canadian Open Neuroscience Platform Poline JB; Das S; Glatard T; Madjar C; Dickie EW; Lecours X; Beaudry T; Beck N; Behan B; Brown ST; Bujold D; Beauvais M; Caron B; Czech C; Dharsee M; Dugré M; Evans K; Gee T; Ippoliti G; Kiar G; Knoppers BM; Kuehn T; Le D; Lo D; Mazaheri M; MacFarlane D; Muja N; O' Brien EA; O' Callaghan L; Paiva S; Park P; Quesnel D; Rabelais H; Rioux P; Legault M; Tremblay-Mercier J; Rotenberg D; Stone J; Strauss T; Zaytseva K; Zhou J; Duchesne S; Khan AR; Hill S; Evans AC; 37024500
ENCS
3 Numerical uncertainty in analytical pipelines lead to impactful variability in brain networks Kiar G; Chatelain Y; de Oliveira Castro P; Petit E; Rokem A; Varoquaux G; Misic B; Evans AC; Glatard T; 34724000
ENCS
4 File-based localization of numerical perturbations in data analysis pipelines. Salari A, Kiar G, Lewis L, Evans AC, Glatard T 33269388
ENCS
5 Comparing perturbation models for evaluating stability of neuroimaging pipelines. Kiar G, de Oliveira Castro P, Rioux P, Petit E, Brown ST, Evans AC, Glatard T 32831546
IMAGING
6 Boutiques: a flexible framework to integrate command-line applications in computing platforms. Glatard T, Kiar G, Aumentado-Armstrong T, Beck N, Bellec P, Bernard R, Bonnet A, Brown ST, Camarasu-Pop S, Cervenansky F, Das S, Ferreira da Silva R, Flandin G, Girard P, Gorgolewski KJ, Guttmann CRG, Hayot-Sasson V, Quirion PO, Rioux P, Rousseau MÉ, Evans AC 29718199
ENCS
7 A Serverless Tool for Platform Agnostic Computational Experiment Management. Kiar G, Brown ST, Glatard T, Evans AC 30890927
ENCS

 

Title:File-based localization of numerical perturbations in data analysis pipelines.
Authors:Salari AKiar GLewis LEvans ACGlatard T
Link:https://www.ncbi.nlm.nih.gov/pubmed/33269388
DOI:10.1093/gigascience/giaa106
Publication:GigaScience
Keywords:NeuroimagingOperating SystemsPipelinesReproducibility
PMID:33269388 Category:Gigascience Date Added:2020-12-04
Dept Affiliation: ENCS
1 Department of Computer Science and Software Engineering, Concordia University, Montreal, QC, Canada.
2 Department of Biomedical Engineering, McGill University, Montreal, QC, Canada.
3 Montreal Neurological Institute, McGill University, Montreal, QC, Canada.

Description:

File-based localization of numerical perturbations in data analysis pipelines.

Gigascience. 2020 Dec 02; 9(12):

Authors: Salari A, Kiar G, Lewis L, Evans AC, Glatard T

Abstract

BACKGROUND: Data analysis pipelines are known to be affected by computational conditions, presumably owing to the creation and propagation of numerical errors. While this process could play a major role in the current reproducibility crisis, the precise causes of such instabilities and the path along which they propagate in pipelines are unclear.

METHOD: We present Spot, a tool to identify which processes in a pipeline create numerical differences when executed in different computational conditions. Spot leverages system-call interception through ReproZip to reconstruct and compare provenance graphs without pipeline instrumentation.

RESULTS: By applying Spot to the structural pre-processing pipelines of the Human Connectome Project, we found that linear and non-linear registration are the cause of most numerical instabilities in these pipelines, which confirms previous findings.

PMID: 33269388 [PubMed - in process]





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