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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)."
Derniers dépôts
Jane Marchand, Jérôme Buire, Vincent Debusschere, Nabil El Jarrai, Jean Pompee, et al.. USING LOCAL RENEWABLE ENERGY TO ENERGISE A MICROGRID: IMPACT OF THE SHARE OF GRID FORMING INVERTERS. 27th International Conference on Electricity Distribution (CIRED 2023), Jun 2023, Rome, Italy. pp.10338, ⟨10.1049/icp.2023.0449⟩. ⟨hal-04134420⟩ Giuseppe Costantino, Sophie Giffard-Roisin, Mauro Dalla Mura, Anne Socquet. Denoising of geodetic time series using spatiotemporal graph neural networks : application to slow slip event extraction. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2024, 17, pp.17567-17579. ⟨10.1109/jstars.2024.3465270⟩. ⟨hal-04880304⟩
Collaborations
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Number of references
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Keywords
Representation learning
Deep learning DL
Artificial intelligence
Spectral clustering
Telemonitoring
Machine Learning
Endmember variability
Hyperspectral
Self-supervised learning
Task analysis
Administrative health database
Evaluation
EEG
Detectors
Output feedback
Alternating direction method of multipliers ADMM
Predictive coding
Speech production
Chronic obstructive pulmonary disease
Speech synthesis
Super-resolution
Continuous positive airway pressure
Remote sensing
Convex optimization
Image processing
Deep Learning
Kernel methods
Co-design
Pansharpening
Spatial resolution
Data models
Automatic speech recognition
Adherence
Data analysis
Fairness
Multispectral
Data fusion
Stochastic approximation
Neural networks
Convolutional neural networks
EHealth
Sleep apnea
Data mining
Generative models
Ethique de l'intelligence artificielle
Image fusion
Nash equilibrium
Asymptotic stability
Feature extraction
Backstepping
Unsupervised learning
Audio-visual speech enhancement
Dimensionality reduction
Scheduling
Big data
Dictionaries
Agricultural exposome
Privacy
Computer vision
Artificial Intelligence
Manifold learning
Training
Infinite-dimensional systems
Sex differences
Image segmentation
Remote sensing RS
Correlation
Algorithmes
Image reconstruction
Hyperspectral imaging
Digital public health
Object detection
Ethics
Prediction
Online learning
Autism
OSA
Classification
Stabilization
Convolution
Intelligence artificielle
Éthique
Random matrix theory
COVID-19
Deep learning
Innovation
Optimal control
Hyperspectral image
Simulation
Philosophie des techniques
Brain
Speech motor control
Optimization
Spatial frequencies
Stochastic differential equations
Digital health e-health
Semantic segmentation
Santé numérique
Optimal controller
Machine learning