4 papers
Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics
Gregory Kiar, Yohan Chatelain, Ali Salari +2
Machine learning models are commonly applied to human brain imaging datasets in an effort to associate function or structure with behaviour, health, or other individual phenotypes.…
Accurate simulation of operating system updates in neuroimaging using Monte-Carlo arithmetic
Ali Salari, Yohan Chatelain, Gregory Kiar +1
Operating system (OS) updates introduce numerical perturbations that impact the reproducibility of computational pipelines. In neuroimaging, this has important practical implicatio…
File-based localization of numerical perturbations in data analysis pipelines
Ali Salari, Gregory Kiar, Lindsay Lewis +2
Data analysis pipelines are known to be impacted by computational conditions, presumably due to the creation and propagation of numerical errors. While this process could play a ma…
Predicting computational reproducibility of data analysis pipelines in large population studies using collaborative filtering
Soudabeh Barghi, Lalet Scaria, Ali Salari +1
Evaluating the computational reproducibility of data analysis pipelines has become a critical issue. It is, however, a cumbersome process for analyses that involve data from large…