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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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Rachel Bawden, Ziqian Peng, Maud Bénard, Eric Villemonte de La Clergerie, Raphaël Esamotunu, et al.. Translate your Own: a Post-Editing Experiment in the NLP domain. The 25th Annual Conference of the European Association for Machine Translation, European Association for Machine Translation, Jun 2024, Sheffield, United Kingdom. ⟨hal-04573922⟩
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Niyati Bafna, Cristina España-Bonet, Josef van Genabith, Benoît Sagot, Rachel Bawden. When your Cousin has the Right Connections: Unsupervised Bilingual Lexicon Induction for Related Data-Imbalanced Languages. LREC-Coling 2024 - Joint International Conference on Computational Linguistics, Language Resources and Evaluation, May 2024, Torino, Italy. ⟨hal-04523029⟩
Keywords
FOS Mathematics
Computer Vision
Inverse problems
Riemannian geometry
Representation learning
Loss function
Dementia
Poetry generation
Prediction
Medical imaging
Image synthesis
Electronic health records
MRI
Human-in-the-loop
Natural language processing
Longitudinal data
Robustness
Artificial intelligence
Self-supervised learning
Machine Learning
Classification
Exoplanet detection
Adaptation
Cancer
Genomics
Language models
Longitudinal study
Neural networks
Validation
Functional connectivity
Reproducibility
Cross-validation
First-order methods
Disease progression modeling
Interpretability
PQA
Optimization
Graph alignment
Alzheimer's Disease
HIV
Curvature penalization
Deep generative models
Huntington's disease
Mixture models
Alzheimer's disease
Portraits
Whole slide images
Provenance
Microscopy
Multiple sclerosis
Wavelets
Online learning
Image processing
Machine learning
Alzheimer’s disease
Breast cancer
Language acquisition
Optimization and Control mathOC
Machine translation
Data visualization
BERT
MT
Direct access
Computational Pathology
Reinforcement learning
Computer vision
Neuroimaging
Brain
Bias
Object detection
Deep Learning
Magnetic resonance imaging
Kalman filter
Robotics
Conjunctive queries
PET
Ensemble learning
Computational modeling
Multiple Sclerosis
Stochastic optimization
Evaluation
Literature
Fluorescence microscopy
French
Brain MRI
Portrait quality assessment
Computational pathology
Action recognition
Variational inference
Image quality assessment
Kernel methods
Segmentation
Hippocampus
Large language models
Clustering
Variational autoencoder
Data imputation
Deep learning
Dimensionality reduction
Language Model