1 code implementation • 28 Mar 2024 • Sana Ahmadi, Pierre Bellec, Tristan Glatard
This paper evaluates different parallelization techniques to reduce the training time of brain encoding with ridge regression on the CNeuroMod Friends dataset, one of the largest deep fMRI resource currently available.
1 code implementation • 3 Apr 2023 • Maximilien Le Clei, Pierre Bellec
There is a recent surge in interest for imitation learning, with large human video-game and robotic manipulation datasets being used to train agents on very complex tasks.
1 code implementation • 3 Apr 2023 • Maximilien Le Clei, Pierre Bellec
Simple evolutionary algorithms have recently been shown to also be capable of optimizing deep neural network parameters, at times matching the performance of gradient-based techniques, e. g. in reinforcement learning settings.
no code implementations • NeurIPS 2019 • Pierre Bellec, Arun Kuchibhotla
Such first order expansion implies that the risk of $\hat{\beta}$ is asymptotically the same as the risk of $\eta$ which leads to a precise characterization of the MSE of $\hbeta$; this characterization takes a particularly simple form for isotropic design.
no code implementations • NeurIPS Workshop Neuro_AI 2019 • Pravish Sainath, Pierre Bellec, Guillaume Lajoie
We train these neural networks to solve the working memory task by training them with a sequence of images in supervised and reinforcement learning settings.
no code implementations • NeurIPS Workshop Neuro_AI 2019 • Yu Zhang, Pierre Bellec
In this project, we applied graph convolutional networks (GCN) to decode brain activity over short time windows in a task fMRI dataset, i. e. associate a given window of fMRI time series with the task used.
no code implementations • 21 Dec 2017 • Christian Dansereau, Angela Tam, AmanPreet Badhwar, Sebastian Urchs, Pierre Orban, Pedro Rosa-Neto, Pierre Bellec
Early prognosis of Alzheimer's dementia is hard.
no code implementations • 12 Jul 2016 • Christian Dansereau, Yassine Benhajali, Celine Risterucci, Emilio Merlo Pich, Pierre Orban, Douglas Arnold, Pierre Bellec
We then implemented a series of Monte-Carlo simulations, based on real data, to evaluate the impact of the multisite effects on detection power in statistical tests comparing two groups (with and without the effect) using a general linear model, as well as on the prediction of group labels with a support-vector machine.
1 code implementation • 21 Jan 2015 • Guillaume Marrelec, Arnaud Messé, Pierre Bellec
We found that the Bayesian formulation naturally shrinks the empirical covariance matrix towards a matrix set a priori (e. g., the identity), provides an automated stopping rule, and corrects for dimensionality using a term that scales up the measure as a function of the dimensionality of the variables.