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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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Remote sensing Neural networks Discrete event simulation Machine Learning Deep neural network Variational auto-encoder Deep learning DL Language documentation Deep learning Data fusion Dictionary learning AI Governance Convolutional Neural Network Audio-visual speech enhancement Fairness Convex optimization Formal Concept Analysis Multispectral Artificial Intelligence Emotional facial expressions Berth allocation Autism spectrum disorder Computational Language Documentation Asymptotic normality Alignment repair Cross modality Computer ethics Big data Alternating direction method of multipliers Optimal control Feature learning Artificial intelligence Acoustic unit discovery Speech enhancement Spectral clustering Dictionaries Hyperspectral imaging Air pollution Hyperspectral Inverse regression Joint learning Ontology alignment Machine learning Automatic speech recognition Adaptation models Allocation des postes à quai Allocation des planches End-to-end system Spectral unmixing Community detection Intelligence artificielle Sequence-to-sequence models Anesthesia Dynamic Epistemic Logic Dysgraphia CPAP Biometrics Random matrix theory Attention Eigenvalues and eigenfunctions Concentration of measure Ethics Representation learning Deep Learning Closed loop systems 62L20 Extended Kalman Filter Manifold learning Attention mechanism Unsupervised learning Semantic segmentation Endmember variability Variational inference Agent communication Fusion Multi-agent systems Mathematical model Stochastic approximation Correlation Graph signal processing Generative models Artificial neural networks Autoencoder Algorithms Europe Remote sensing RS Sleep apnea Adherence Dynamic binary translation Smoothing Laycan allocation MRI Expectation-maximization Classification Random spanning forests COVID-19 Task analysis Dimensionality reduction Delays Computational language documentation