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3IA Côte d'Azur - Interdisciplinary Institute for Artificial Intelligence
3IA Côte d'Azur est l'un des quatre "Instituts interdisciplinaires d'intelligence artificielle" créés en France en 2019. Son ambition est de créer un écosystème innovant et influent au niveau local, national et international. L'institut 3IA Côte d'Azur est piloté par Université Côte d'Azur en partenariat avec les grands partenaires de l'enseignement supérieur et de la recherche de la région niçoise et de Sophia Antipolis : CNRS, Inria, INSERM, EURECOM, SKEMA Business School. L'institut 3IA Côte d'Azur est également soutenu par l'ECA, le CHU de Nice, le CSTB, le CNES, l'Institut Data ScienceTech et l'INRAE. Le projet a également obtenu le soutien de plus de 62 entreprises et start-ups.
Derniers dépôts
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Iker García-Ferrero, Rodrigo Agerri, Aitziber Atutxa, Elena Cabrio, Iker de la Iglesia, et al.. Medical mT5: An Open-Source Multilingual Text-to-Text LLM for The Medical Domain. LREC-COLING 2024 - 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, May 2024, TORINO, Italy. ⟨hal-04603270⟩
Documents en texte intégral
653
Notices
301
Statistiques par discipline
Mots clés
Embedded Systems
Ontology Learning
Artificial Intelligence
FPGA
Consensus
MRI
Electronic medical record
Hyperbolic systems of conservation laws
Differential privacy
Apprentissage profond
Computational Topology
Extracellular matrix
Electrophysiology
Co-clustering
Predictive model
Data augmentation
Extreme value theory
COVID-19
53B20
Linked Data
Argument Mining
Explainable AI
Convolutional neural networks
Topological Data Analysis
Simulations
Optimization
NLP Natural Language Processing
Unsupervised learning
Alzheimer's disease
Macroscopic traffic flow models
Dense labeling
Brain-inspired computing
Computer vision
Semantic segmentation
Grammatical Evolution
OPAL-Meso
Atrial fibrillation
Latent block model
Diffusion MRI
Federated Learning
Dimensionality reduction
Atrial Fibrillation
Image fusion
Isomanifolds
Medical imaging
Machine learning
Physics-based learning
RDF
Multiple Sclerosis
Anomaly detection
Segmentation
Neural networks
CNN
Persistent homology
Multi-Agent Systems
Hyperspectral data
Domain adaptation
Knowledge graph
SPARQL
Sparsity
Fibronectin
Graph neural networks
Cable-driven parallel robot
Deep learning
Convolutional Neural Networks
Uncertainty
Artificial intelligence
Excursion sets
Diffusion strategy
Spiking Neural Networks
Linked data
Semantic web
Autonomous vehicles
Super-resolution
Echocardiography
Deep Learning
Healthcare
Spiking neural networks
Clinical trials
Coxeter triangulation
Clustering
Event cameras
Web of Things
Fluorescence microscopy
Convolutional neural network
Distributed optimization
Privacy
Biomarkers
Visualization
Convergence analysis
Image segmentation
Autoencoder
Contrastive learning
Information Extraction
Federated learning
Knowledge graphs
Semantic Web
Arguments
Computing methodologies
Electrocardiogram