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Welcome to the HAL Open Archive collection of the National Research Programme for AI (NRPIA). This collection aims to gather the publications from the projects financed by the NRPIA and available at HAL.

In the closing day of « AI for Humanity » debate held in Paris on March 29, 2018, the President of the French Republic presented an ambitious strategy for Artificial Intelligence (AI) and launched the National AI strategy.

The National AI strategy will mobilise a budget of €1.5 billion over the period 2018-2022, 45% of which will be devoted to research. As part of the AI for Humanity Plan, Inria was commissioned to coordinate the research component of the national AI program.

The objective of the National AI Research Programme is twofold: to sustainably establish France as one of the top 5 countries in AI and to make France the European leader in research in AI. To this aim, several actions will be carried out in a first phase extending from the end of 2018 to 2022 (4 Interdisciplinary Institutes, chairs, doctoral contracts, training, computing resources, ANR calls, public-private partnerships and international cooperation).

For further information on the National AI Research Programme, visit the site web.

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Medical imaging Possibility theory Distributed optimization Mixture models Macroscopic traffic flow models Visualization Ethics Computer vision Spectral clustering Graph signal processing Computational modeling Convolutional neural network Matrix factorization Clinical trials Privacy Community detection Segmentation Semidefinite programming Computational Topology Diffusion strategy Data visualization Remote sensing Data fusion Convolution Neural Networks Prediction Reinforcement learning Neural networks Spectral unmixing Machine Learning Explainable AI Online learning Image processing Dimensionality reduction MRI Convolutional Neural Networks Argumentation Generative models Stochastic optimization Manifold learning Uncertainty Image segmentation Kernel methods Optimization Intelligence artificielle Image analysis Deep Learning Clustering Stochastic approximation Riemannian geometry Representation learning Polynomial optimization Alzheimer's disease Random matrix theory Semantic segmentation Fairness Discrete event simulation Automatic speech recognition Hyperspectral imaging Autonomous vehicles Image fusion Éthique Excursion sets Conflict resolution Machine learning Autoencoder Convolutional neural networks Data augmentation Classification Convex optimization Simulation Super-resolution Spiking neural networks OPAL-Meso EEG Big data Domain adaptation Diffusion MRI Artificial intelligence Semantic Web Endmember variability Linked Data Multispectral Unsupervised learning Artificial Intelligence Statistics Deep learning COVID-19 Sparsity Air Traffic Management Dense labeling Bioacoustics Simulated annealing Co-clustering Discrimination Deep learning DL Big Data Hyperspectral Scheduling Global optimization

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