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Welcome on HAL open archive of PaRis AI Research InstitutE
3AI Plan
The Prairie Institute (PaRis AI Research InstitutE) is one of the four French Institutes of Artificial Intelligence, which were created as part of the national French initiative on AI announced by President Emmanuel Macron on May 29, 2018.
A major part of this ambitious plan, which has a total budget of one billion euros, was the creation of a small number of interdisciplinary AI research institutes (or “3IAs” for “Instituts Interdisciplinaires d’Intelligence Artificielle”). After an open call for participation in July 2018 and two rounds of review by an international scientific committee, the Grenoble, Nice, Paris and Toulouse projects have officially received the 3IA label on April 24, 2019, with a total budget of 75 million Euros.
For more information about PaRis AI Research InstitutE, see our web site.
The Prairie Institute (PaRis AI Research InstitutE) is one of the four French Institutes of Artificial Intelligence, which were created as part of the national French initiative on AI announced by President Emmanuel Macron on May 29, 2018.
A major part of this ambitious plan, which has a total budget of one billion euros, was the creation of a small number of interdisciplinary AI research institutes (or “3IAs” for “Instituts Interdisciplinaires d’Intelligence Artificielle”). After an open call for participation in July 2018 and two rounds of review by an international scientific committee, the Grenoble, Nice, Paris and Toulouse projects have officially received the 3IA label on April 24, 2019, with a total budget of 75 million Euros.
For more information about PaRis AI Research InstitutE, see our web site.
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Francesco Galati, Daniele Falcetta, Rosa Cortese, Barbara Casolla, Ferran Prados, et al.. A2V: A Semi-Supervised Domain Adaptation Framework for Brain Vessel Segmentation via Two-Phase Training Angiography-to-Venography Translation. BMVC 2023, 34th British Machine Vision Conference, Nov 2023, Aberdeen, United Kingdom. ⟨hal-04195756v2⟩
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Ravi Hassanaly, Camille Brianceau, Olivier Colliot, Ninon Burgos. Unsupervised anomaly detection in 3D brain FDG PET: A benchmark of 17 VAE-based approaches. Deep Generative Models workshop at the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023), Oct 2023, Vancouver, Canada. ⟨hal-04185304⟩
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Keywords
Deep learning
Clinical trial
HIV
Variational autoencoder
Microscopy
Object discovery
Magnetic resonance imaging
Alzheimer
Longitudinal study
SmFISH
Computational modeling
Graph alignment
Weakly-supervised learning
Data imputation
Confidence interval
Multiple sclerosis
Dimensionality reduction
French
Wavelets
Zero-Shot Learning
Simulation
Language Model
Adaptation
Multiple Sclerosis
Anatomical MRI
RNA localization
Curvature penalization
Semantics
Sparsity
Alzheimer's disease
Ensemble learning
Stochastic optimization
Machine Learning
Computer vision
PET
Functional connectivity
Self-supervised learning
Cancer
Brain MRI
Neural networks
Electronic health records
Attention Mechanism
Apprentissage faiblement supervisé
Literature
Alzheimer's Disease
Convexity shape prior
BCI
Human-in-the-loop
Reinforcement learning
Kalman filter
CamemBERT
MRI
Riemannian geometry
Brain
Contrastive predictive coding
Interpretability
Choroid plexus
Segmentation
BERT
Clinical data warehouse
Poetry generation
Clustering
Neuroimaging
Computer Vision
Data visualization
Convex optimization
Genomics
Huntington's disease
Apprentissage par renforcement
Machine learning
ASPM
Whole slide images
Deep Learning
Complex systems
Active learning
Alzheimer’s disease
Bayesian logistic regression
Computational Pathology
Mixture models
Longitudinal data
Action recognition
Object detection
Dementia
Representation learning
Image processing
Classification
Hippocampus
Optimization
Image synthesis
Prediction
Clinical Data Warehouse
Breast cancer
Medical imaging
Reproducibility
Artificial intelligence
Bias
Transcriptomics
ADNI
Kernel methods
Association
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