Gregory Kiar | DeepAI

AI Chat

Featured Co-authors

Tristan Glatard
28 publications
Rafael Ferreira da Silva
21 publications
Valérie Hayot-Sasson
12 publications
Tristan Aumentado-Armstrong
11 publications
Pierre Bellec
7 publications
Alan C. Evans
7 publications
Yohan Chatelain
5 publications
Shawn T Brown
5 publications
Pablo De Oliveira Castro
5 publications
Eric Petit
5 publications
Oscar Esteban
4 publications

∙ 08/04/2023

A Parameter-efficient Multi-subject Model for Predicting fMRI Activity

This is the Algonauts 2023 submission report for team "BlobGPT". Our mod...

0 Connor Lane, et al. ∙

∙ 07/03/2023

A numerical variability approach to results stability tests and its application to neuroimaging

Ensuring the long-term reproducibility of data analyses requires results...

0 Yohan Chatelain, et al. ∙

∙ 12/13/2022

Numerical Stability of DeepGOPlus Inference

Convolutional neural networks (CNNs) are currently among the most widely...

0 Inés Gonzalez Pepe, et al. ∙

∙ 12/21/2021

PyTracer: Automatically profiling numerical instabilities in Python

Numerical stability is a crucial requirement of reliable scientific comp...

0 Yohan Chatelain, et al. ∙

∙ 09/20/2021

Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics

Machine learning models are commonly applied to human brain imaging data...

13 Gregory Kiar, et al. ∙

∙ 08/20/2021

A Recommender System for Scientific Datasets and Analysis Pipelines

Scientific datasets and analysis pipelines are increasingly being shared...

0 Mandana Mazaheri, et al. ∙

∙ 06/28/2021

Reducing numerical precision preserves classification accuracy in Mondrian Forests

Mondrian Forests are a powerful data stream classification method, but t...

0 Marc Vicuna, et al. ∙

∙ 02/14/2020

Deploying large fixed file datasets with SquashFS and Singularity

Shared high-performance computing (HPC) platforms, such as those provide...

0 Pierre Rioux, et al. ∙

∙ 08/28/2019

Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging

A lack of software reproducibility has become increasingly apparent in t...

0 Gregory Kiar, et al. ∙

∙ 09/02/2018

A Serverless Tool for Platform Agnostic Computational Experiment Management

Neuroscience has been carried into the domain of big data and high perfo...

0 Gregory Kiar, et al. ∙

∙ 11/08/2017

Boutiques: a flexible framework for automated application integration in computing platforms

We present Boutiques, a system to automatically publish, integrate and e...

0 Tristan Glatard, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world