38 citations · 73 across the 31 of their papers we have counts for
6 papers · 1 filter
Performance Evaluation of Big Data Processing Strategies for Neuroimaging
Valérie Hayot-Sasson, Shawn T Brown, Tristan Glatard
Neuroimaging datasets are rapidly growing in size as a result of advancements in image acquisition methods, open-science and data sharing. However, the adoption of Big Data process…
A multi-dimensional extension of the Lightweight Temporal Compression method
Bo Li, Omid Sarbishei, Hosein Nourani +1
Lightweight Temporal Compression (LTC) is among the lossy stream compression methods that provide the highest compression rate for the lowest CPU and memory consumption. As such, i…
Data models for service failure prediction in supply-chain networks
Monika Sharma, Tristan Glatard, Eric Gelinas +2
We aim to predict and explain service failures in supply-chain networks, more precisely among last-mile pickup and delivery services to customers. We analyze a dataset of 500,000 s…
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…
A Serverless Tool for Platform Agnostic Computational Experiment Management
Gregory Kiar, Shawn T Brown, Tristan Glatard +1
Neuroscience has been carried into the domain of big data and high performance computing (HPC) on the backs of initiatives in data collection and an increasingly compute-intensive…
NeuroStorm: Accelerating Brain Science Discovery in the Cloud
Gregory Kiar, Robert J. Anderson, Alex Baden +24
Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales. However, our ability to capitalize on existing datasets, tools, and intellectual capa…