Loading...
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.
Full text
624
References
624
Last deposit
-
-
Marvin Lavechin, Marianne Métais, Hadrien Titeux, Alodie Boissonnet, Jade Copet, et al.. Brouhaha: multi-task training for voice activity detection, speech-to-noise ratio, and C50 room acoustics estimation. IEEE Automatic Speech Recognition and Understanding (ASRU 2023 ), IEEE, Dec 2023, Taipei, Taiwan. pp.1--7. ⟨hal-04247647⟩
-
-
-
-
-
Keywords
Cancer
CamemBERT
Reinforcement learning
Computer vision
Reproducibility
Clinical data warehouse
Whole slide images
Interpretability
Classification
Adaptation
Image synthesis
Clustering
Cross-validation
Apprentissage faiblement supervisé
Ensemble learning
Dementia
Magnetic resonance imaging
RNA localization
MRI
Artificial intelligence
Prediction
Variational autoencoder
Zero-Shot Learning
Riemannian geometry
Sparsity
Bias
Neuroimaging
Breast cancer
Simulation
Deep learning
Microscopy
Unsupervised anomaly detection
Natural language processing
Machine learning
Alzheimer's disease
Data visualization
Attention Mechanism
Genomics
Data imputation
Mixture models
Image processing
Self-supervised learning
Direct access
Wavelets
Clinical Data Warehouse
Deep Learning
Multiple sclerosis
Action recognition
Optimization
Functional connectivity
Kernel methods
Evaluation
Deep generative models
Apprentissage par renforcement
Segmentation
Alzheimer’s disease
Choroid plexus
Machine translation
Literature
Computer Vision
Variational inference
Bayesian logistic regression
Alzheimer
Active learning
Language acquisition
Dimensionality reduction
Poetry generation
Weakly-supervised learning
French
HIV
Hippocampus
Human-in-the-loop
Brain
Electronic health records
Multiple Sclerosis
Language Model
Graph alignment
Longitudinal study
BERT
Online learning
Longitudinal data
Neural networks
Computational modeling
Stochastic optimization
Huntington's disease
Transcriptomics
Artificial Intelligence
Representation learning
Anatomical MRI
Kalman filter
BCI
Medical imaging
Object detection
Brain MRI
Curvature penalization
ASPM
Machine Learning
ADNI
Alzheimer's Disease
Association
![]() |
![]() |
![]() |
![]() |
![]() |