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MIAI Grenoble Alpes (Multidisciplinary Institute in Artificial Intelligence) aims to conduct research in artificial intelligence at the highest level, to offer attractive courses for students and professionals of all levels, to support innovation in large companies, SMEs and startups and to inform and interact with citizens on all aspects of AI.

The activities of MIAI Grenoble Alpes are structured around two main themes : future AI systems and AI for human beings the environment.

Instructions to authors: If your research work has been supported by the MIAI Grenoble Alpes, please mention in your article:  "This work has been partially supported by MIAI@Grenoble Alpes, (ANR-19-P3IA-0003)."

 

 

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Keywords

Hyperspectral image unmixing Laycan allocation Hyperspectral image Ethics Europe Computational language documentation Graph signal processing Fusion Data fusion Deep Learning LawEnforcement High-dimension Adaptation models Task analysis Discrete event simulation Language documentation Delays AI Governance Deep learning DL Closed loop systems Indoor navigation Convex optimization Audio-visual speech enhancement Dynamic binary translation Light detection and ranging LiDAR Dictionaries Speech enhancement Image processing Attention mechanism Convolutional Neural Network Machine learning Autoencoder Remote sensing Internal Security Infinite-dimensional systems Inverse regression Artificial Intelligence Gestion portuaire Biometrics Artificial intelligence Mathematical model Multispectral ISM molecules Spectral clustering Kernel methods Correlation Anesthesia Hyperspectral Hyperspectral imaging Variational auto-encoder Smoothing Deep neural network Asymptotic normality Eigenvalues and eigenfunctions Allocation des postes à quai Artificial neural networks Random spanning forests Community detection Extended Kalman Filter Machine Learning Intraoperative ultrasound Allocation des planches France Big data Concentration of measure LiDAR Cross modality ISM clouds Deep learning Spectral unmixing Neural networks MRI Sequence-to-sequence models Generative models Hyperspectral images Unsupervised learning Random matrix theory Image fusion Attention Acoustic unit discovery Classification Manifold learning Semantic segmentation Berth allocation Lower complexity bounds Hyperspectral HS Magnetic resonance fingerprinting Representation learning Fairness Stochastic approximation Dimensionality reduction 62L20 COVID-19 Remote sensing RS Dynamic Epistemic Logic Feature learning Alternating direction method of multipliers Low-resource languages Joint learning Endmember variability