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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.

Contact : mission.ia@inria.fr

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Keywords

Ensemble learning Big data Sparsity Data fusion Computer vision Optimal control Evaluation complexity Object detection Medical imaging Convex optimization Image fusion Prediction Graph neural networks Éthique Stability Kernel methods Ethics Feature extraction Macroscopic traffic flow models Generative models Self-supervised learning Task analysis Simulated annealing Computer Vision Semidefinite programming Deep learning DL Uncertainty Intelligence artificielle Natural Language Processing Polynomial optimization Image processing Natural language processing Segmentation Scheduling Constraint programming Explainable AI Semantic segmentation Super-resolution Clustering Dimensionality reduction Remote sensing Reinforcement learning Evaluation Complexity Neural networks MRI Training Deep learning Fairness Linked Data Convolutional neural networks Classification Optimization Machine learning EEG Artificial intelligence Data mining Excursion sets Optimal transport Convolutional Neural Networks Argumentation Neuroimaging Transfer learning Non-convex optimization Artificial Intelligence Endmember variability Neural network Convolution COVID-19 Unsupervised learning Stochastic optimization Simulation Diffusion MRI Online learning Pansharpening Co-clustering Machine translation RDF Privacy FOS Computer and information sciences Variational autoencoder Semantic Web Hyperspectral Interpretability Image segmentation XAI Deep Learning Representation learning Anomaly detection Spectral unmixing Convolutional neural network Fluorescence microscopy Inverse problems Explainability Spiking neural networks Alzheimer's disease Robustness Machine Learning Bias Hyperspectral imaging

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