Loading...
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
-
Rémi Felin, Pierre Monnin, Catherine Faron, Andrea G. B. Tettamanzi. RDFminer: an Interactive Tool for the Evolutionary Discovery of SHACL Shapes. The Semantic Web - 21st International Conference, ESWC 2024, May 2024, Hersonissos (Crete), Greece. The Semantic Web - 21st International Conference, ESWC 2024, Hersonissos, Crete, Greece, May 26 - May 30, 2024, Proceedings. ⟨hal-04566981⟩
-
Célian Ringwald. Learning Pattern-Based Extractors from Natural Language and Knowledge Graphs: Applying Large Language Models to Wikipedia and Linked Open Data. Proceedings of the 38th AAAI Conference on Artificial Intelligence, Feb 2024, Vancouver, France. pp.23411-23412, ⟨10.1609/aaai.v38i21.30406⟩. ⟨hal-04526050⟩
-
Celian Ringwald, Fabien Gandon, Catherine Faron, Franck Michel, Hanna Abi Akl. Learning Pattern-Based Extractors from Natural Language and Knowledge Graphs Applying Large Language Models to Wikipedia & the Linked Open Data (POSTER). AAAI 2024 - 38th Annual AAAI Conference on Artificial Intelligence, Feb 2024, Vancouver, France. . ⟨hal-04526139⟩
-
Celian Ringwald, Fabien Gandon, Catherine Faron, Franck Michel, Hanna Abi Akl. Well-written Knowledge Graphs Most Effective RDF Syntaxes for Triple Linearization in End-to-End Extraction of Relations from Text (Student Abstract). AAAI 24 - 38th Annual AAAI Conference on Artificial Intelligence, Feb 2024, Vancouver, Canada. . ⟨hal-04526132⟩
Documents en texte intégral
641
Notices
299
Statistiques par discipline
Mots clés
Convergence analysis
Computer vision
Convolutional Neural Networks
Apprentissage profond
Diffusion MRI
Multiple Sclerosis
Contrastive learning
MRI
Segmentation
Autonomous vehicles
Convolutional neural networks
Ontology Learning
NLP Natural Language Processing
Latent block model
Graph neural networks
Differential privacy
Linked data
Hyperbolic systems of conservation laws
Clinical trials
FPGA
53B20
Extreme value theory
Predictive model
Clustering
Healthcare
Crossings
Convolutional neural network
Domain adaptation
Data augmentation
Macroscopic traffic flow models
Embedded Systems
Semantic segmentation
Artificial intelligence
Arguments
Atrial fibrillation
Deep learning
Alzheimer's disease
Linked Data
Brain-inspired computing
RDF
Neural networks
OPAL-Meso
CNN
Dimensionality reduction
Extracellular matrix
Information Extraction
Diffusion strategy
Grammatical Evolution
Autoencoder
Computing methodologies
Machine learning
Semantic Web
Explainable AI
Dense labeling
Coxeter triangulation
Fluorescence microscopy
Electrophysiology
Spiking Neural Networks
Hyperspectral data
Simulations
Anomaly detection
Federated Learning
Deep Learning
COVID-19
Biomarkers
Optimization
Medical imaging
Topological Data Analysis
Binary image
Computational Topology
Event cameras
Consensus
Isomanifolds
Electrocardiogram
Image segmentation
Semantic web
Cable-driven parallel robot
Electronic medical record
Multi-Agent Systems
Privacy
Sparsity
Echocardiography
Argument Mining
Excursion sets
Uncertainty
Web of Things
Co-clustering
Persistent homology
Super-resolution
Federated learning
Atrial Fibrillation
Unsupervised learning
Artificial Intelligence
Image fusion
Physics-based learning
Knowledge graphs
Distributed optimization
Knowledge graph
Spiking neural networks
Visualization