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OPAL
OPAL (Observatoire Pluridisciplinaire des Alpes-maritimes) est un équipement de calcul haute-performance (HPC) dédié à la recherche, l’intelligence artificielle (IA), le calcul, le stockage de données et la visualisation. OPAL est une convention entre Université Côte d'Azur, Observatoire de la Côte d'Azur, Inria Sophia Antipolis et Mines ParisTech à Sophia Antipolis. Son principe repose sur la mutualisation des ressources de calcul de ces quatre institutions grâce à un accès unifié. OPAL offre des possibilités de calcul aux membres d’Université Côte d'Azur et à leurs partenaires industriels pour la recherche, l’éducation et le développement.
Derniers dépôts
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Angelo Rodio, Giovanni Neglia, Fabio Busacca, Stefano Mangione, Sergio Palazzo, et al.. Federated Learning with Packet Losses. WPMC 2023 - 26th International Symposium on Wireless Personal Multimedia Communications, Nov 2023, Tampa, United States. pp.1-6, ⟨10.1109/WPMC59531.2023.10338845⟩. ⟨hal-04364289⟩
Documents en texte intégral
250
Notices
20
Statistiques par discipline
Mots clés
Neural networks
Multi-View
Marked point process
Multiple Sclerosis
Stars atmospheres
Deep Learning
Federated Learning
CNN
PET Imaging
Astrophysics - Solar and Stellar Astrophysics
Structural Connectivity
Tractography
Image processing
Schwarz method
Remote Sensing
Lithospheric
Multigrid method
Minor planets
Turbulence
A posteriori estimate
Reconstruction
3D reconstruction
Alps
Finite element method
Imagerie sismique
Inversion de formes d'ondes
Lithosphérique
Methods observational
Seismic imaging
Protoplanetary disks
Semantic segmentation
Convolutional neural networks
Stars fundamental parameters
Event camera
Generative adversarial networks
EEG
MEG
GANs
Sketch-based modeling
Gaussian Process
Alpes
Methods statistical
Attention
Neuromorphic
Stable decomposition
Controlled source seismology
Galaxy evolution
Methods numerical
Plasmas
Alzheimer's disease
Convolutional neural network
Line drawing
GM-PHD
Spherical Harmonics
Object detection
SVBRDF
Galaxy abundances
Saliency
Mean-field limit
Point process
Appearance capture
Densité
Image-Based Rendering
Catastrophic forgetting
Radiative transfer
Machine learning
Segmentation
Dense labeling
Planets and satellites formation
Méthodes directes
Non-photorealistic rendering
Remote sensing
Gravitation
Domain adaptation
Hydrodynamics
Full-waveform inversion
Tomographie
Gaunt Coefficients
Computer Graphics
Planets and satellites dynamical evolution and stability
Atherosclerosis
Deep learning
Action Detection
OPAL-Meso
Sketching
Compound regularization
Planets and satellites detection
Small object detection
Planet-disk interactions
Galaxy disk
Stars abundances
Material capture
$p$-robustness
Neural Rendering
Astrophysics - Earth and Planetary Astrophysics
Density
Stars activity
Instabilities
Inverse theory
Diffusion MRI