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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
Curvature penalization
Computer Vision
Semantics
Transcriptomics
Human-in-the-loop
Brain MRI
Zero-Shot Learning
Huntington's disease
Classification
Wavelets
Clinical data warehouse
Convexity shape prior
Anatomical MRI
CamemBERT
Hippocampus
Weakly-supervised learning
Alzheimer’s disease
Representation learning
Sparsity
Clinical trial
Stochastic optimization
Brain
Optimization
Language Model
Breast cancer
Data imputation
Attention Mechanism
Clinical Data Warehouse
Adaptation
Alzheimer's disease
Simulation
Dementia
Mixture models
Microscopy
Convex optimization
Contrastive predictive coding
Literature
Complex systems
Genomics
Object detection
Ensemble learning
BCI
Choroid plexus
Deep Learning
Image processing
Confidence interval
Deep learning
Reproducibility
Variational autoencoder
Kalman filter
Kernel methods
Action recognition
ASPM
Multiple sclerosis
Machine Learning
Computational modeling
Segmentation
French
Clustering
Electronic health records
Artificial intelligence
Alzheimer's Disease
Apprentissage par renforcement
RNA localization
Magnetic resonance imaging
Longitudinal data
Cancer
Riemannian geometry
Self-supervised learning
ADNI
Multiple Sclerosis
Whole slide images
Prediction
Data visualization
Neural networks
Active learning
Graph alignment
BERT
Bayesian logistic regression
Dimensionality reduction
Object discovery
PET
Reinforcement learning
Bias
SmFISH
Functional connectivity
Interpretability
Neuroimaging
Image synthesis
Computational Pathology
Poetry generation
Association
Apprentissage faiblement supervisé
HIV
Longitudinal study
Medical imaging
MRI
Machine learning
Computer vision
Alzheimer
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