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The 3AI plan  

The Prairie Institute (PaRis AI Research InstitutE) is one of the four French Institutes of Artificial Intelligence, which were created as part of the national French initiative on AI announced by President Emmanuel Macron on May 29, 2018.
A major part of this ambitious plan, which has a total budget of one billion euros, was the creation of a small number of interdisciplinary AI research institutes (or “3IAs” for “Instituts Interdisciplinaires d’Intelligence Artificielle”). After an open call for participation in July 2018 and two rounds of review by an international scientific committee, the Grenoble, Nice, Paris and Toulouse projects have officially received the 3IA label on April 24, 2019, with a total budget of 75 million Euros.

For more information about PaRis AI Research InstitutE, see our website.


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Functional connectivity Cancer Adaptation Computer Vision Alzheimer's Disease Convex optimization Longitudinal analysis Image processing Imitation learning Clinical data warehouse Longitudinal data MRI Digital Humanities Self-supervised learning Magnetic resonance imaging Artificial intelligence Deep Learning Curvature penalization Representation learning Dementia Optimization Anatomical MRI Ensemble learning Mixed-effects models High-dimensional data Bayesian logistic regression Mixture models Impulse control disorders Data imputation Data treatment Graphical models Alzheimer’s disease Independent Component Analysis Manifold learning Deep learning Inverse problems Local translation Wavelets Image synthesis Genomics Medical imaging ADNI Longitudinal study Kernel methods Alzheimer's disease Data visualization ASPM Brain Human-in-the-loop Segmentation Language Modeling Association Machine Learning Eikonal equation HIV Prediction Vision par ordinateur Intrinsic dimension Disease progression model Virtual reality Clustering Robotics Graph alignment Convexity shape prior Contrastive predictive coding Erdős-Rényi random graphs French Poetry generation Data Augmentation Transcriptomics BERT Speech perception Dimensionality reduction Data leakage Riemannian geometry Classification Microscopy Interpretability Speech recognition Brain MRI Emergence Stochastic optimization First-order methods BCI Diabetes Idiolect Computer vision Literature Machine learning High Content Screening Reproducibility Object detection Cross-cohort replication Neuroimaging Computational modeling Bias Kalman filter Evaluation metrics MCMC-SAEM Action recognition



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