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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
Gaussian Process
EEG
Methods statistical
Small object detection
Planets and satellites detection
Minor planets
Galaxy evolution
Neuromorphic
Convolutional neural network
Controlled source seismology
Inversion de formes d'ondes
Generative adversarial networks
Federated Learning
Density
Planet-disk interactions
Instabilities
A posteriori estimate
Attention
Structural Connectivity
Alzheimer's disease
Atherosclerosis
MEG
Semantic segmentation
GANs
Methods numerical
SVBRDF
Action Detection
Methods observational
Image processing
Alps
Alpes
Material capture
Inverse theory
Protoplanetary disks
Multi-View
CNN
Line drawing
Remote sensing
Astrophysics - Solar and Stellar Astrophysics
Galaxy disk
Remote Sensing
Machine learning
Densité
Stable decomposition
Reconstruction
Astrophysics - Earth and Planetary Astrophysics
Full-waveform inversion
Point process
Appearance capture
Gaunt Coefficients
Planets and satellites formation
Object detection
Stars fundamental parameters
Sketching
Sketch-based modeling
Neural Rendering
Seismic imaging
Finite element method
Computer Graphics
Tomographie
Deep learning
Event camera
Galaxy abundances
Marked point process
Convolutional neural networks
$p$-robustness
Turbulence
Non-photorealistic rendering
Domain adaptation
Diffusion MRI
Spherical Harmonics
Méthodes directes
Lithospheric
GM-PHD
Stars abundances
Hydrodynamics
Multiple Sclerosis
Stars atmospheres
Saliency
Catastrophic forgetting
Compound regularization
Lithosphérique
Segmentation
OPAL-Meso
Planets and satellites dynamical evolution and stability
Neural networks
Radiative transfer
Gravitation
Plasmas
Dense labeling
Image-Based Rendering
Schwarz method
Multigrid method
Stars activity
Imagerie sismique
Tractography
PET Imaging
Deep Learning
3D reconstruction
Mean-field limit