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



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