Gregory Kiar

Orcid: 0000-0001-8915-496X

According to our database1, Gregory Kiar authored at least 55 papers between 2017 and 2023.

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Bibliography

2023
bids-specification.
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Dataset, November, 2023

nilearn.
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Dataset, October, 2023




PyTracer: Automatically Profiling Numerical Instabilities in Python.
IEEE Trans. Computers, June, 2023



A Parameter-efficient Multi-subject Model for Predicting fMRI Activity.
CoRR, 2023

A numerical variability approach to results stability tests and its application to neuroimaging.
CoRR, 2023

2022






Numerical Stability of DeepGOPlus Inference.
CoRR, 2022

Pipeline-Invariant Representation Learning for Neuroimaging.
CoRR, 2022

2021




Eliminating accidental deviations to minimize generalization error and maximize replicability: Applications in connectomics and genomics.
PLoS Comput. Biol., 2021

PyTracer: Automatically profiling numerical instabilities in Python.
CoRR, 2021

Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics.
CoRR, 2021

A Recommender System for Scientific Datasets and Analysis Pipelines.
Proceedings of the 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 2021

Accurate Simulation of Operating System Updates in Neuroimaging Using Monte-Carlo Arithmetic.
Proceedings of the Uncertainty for Safe Utilization of Machine Learning in Medical Imaging, and Perinatal Imaging, Placental and Preterm Image Analysis, 2021

Reducing numerical precision preserves classification accuracy in Mondrian Forests.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

2020







Brain status modeling with non-negative projective dictionary learning.
NeuroImage, 2020

Comparing perturbation models for evaluating stability of neuroimaging pipelines.
Int. J. High Perform. Comput. Appl., 2020

A Quantitative EEG Toolbox for the MNI Neuroinformatics Ecosystem: Normative SPM of EEG Source Spectra.
Frontiers Neuroinformatics, 2020

Deploying large fixed file datasets with SquashFS and Singularity.
Proceedings of the PEARC '20: Practice and Experience in Advanced Research Computing, 2020

2019










PyBIDS: Python tools for BIDS datasets.
J. Open Source Softw., 2019

A Serverless Tool for Platform Agnostic Computational Experiment Management.
Frontiers Neuroinformatics, 2019

Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging.
CoRR, 2019

2018
Container-Based Clinical Solutions for Portable and Reproducible Image Analysis.
J. Digit. Imaging, 2018

2017
BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods.
PLoS Comput. Biol., 2017

Boutiques: a flexible framework for automated application integration in computing platforms.
CoRR, 2017


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