Author(s): Gonzalez Pepe I; Chatelain Y; Kiar G; Glatard T;

Convolutional neural networks (CNNs) are currently among the most widely-used deep neural network (DNN) architectures available and achieve state-of-the-art performance for many problems. Originally applied to computer vision tasks, CNNs work well with any data with a spatial relationship, besides images, and have been applied to different fields. However ...

Article GUID: 38285635

Author(s): 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 ...

We present the Canadian Open Neuroscience Platform (CONP) portal to answer the research community's need for flexible data sharing resources and provide advanced tools for search and processing infrastructure capacity. This portal differs from previous data sharing projects as it integrates d ...

Article GUID: 37024500

Author(s): Kiar G; Chatelain Y; de Oliveira Castro P; Petit E; Rokem A; Varoquaux G; Misic B; Evans AC; Glatard T;

The analysis of brain-imaging data requires complex processing pipelines to support findings on brain function or pathologies. Recent work has shown that variability in analytical decisions, small amounts of noise, or computational environments can lead to substantial differences in the results, ...

Article GUID: 34724000

Author(s): Salari A, Kiar G, Lewis L, Evans AC, Glatard T

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: ...

Article GUID: 33269388

Author(s): Kiar G, de Oliveira Castro P, Rioux P, Petit E, Brown ST, Evans AC, Glatard T

With an increase in awareness regarding a troubling lack of reproducibility in analytical software tools, the degree of validity in scientific derivatives and their downstream results has become unclear. The nature of reproducibility issues may vary across domains, tools, data sets, and computational infrastructures, but numerical instabilities are though ...

Article GUID: 32831546

Author(s): 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, ...

Gigascience. 2018 05 01;7(5): Authors: 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, E ...

Article GUID: 29718199

Author(s): Kiar G, Brown ST, Glatard T, Evans AC

Front Neuroinform. 2019;13:12 Authors: Kiar G, Brown ST, Glatard T, Evans AC

Article GUID: 30890927