Projects

Frugal AI and Embedded AI

ADAPTING
ADAPTING
An approach that goes further than current hardware architectures, with the aim of reaching the next generation of AI applications.
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EMERGENCES
EMERGENCES
Near-physics emerging models for embedded AI
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HOLIGRAIL
HOLIGRAIL
Hollistic approaches to greener model architectures for inference and learning
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SHARP
SHARP
Sharp theoretical and algorithmic principles for frugal ML
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Trustworthy AI and Distributed AI

CAUSALI-T-AI
CAUSALI-T-AI
When causality and AI teams up to enhance interpretability and robustness of AI algorithms
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FOUNDRY
FOUNDRY
The foundations of robustness and reliability in artificial intelligence
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REDEEM
REDEEM
Resilient, decentralized and privacy-preserving machine learning
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SAIF
SAIF
Safe AI through formal methods
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New Mathematical Foundations of AI

PDE-AI
PDE-AI
Numerical analysis, optimal control and optimal transport for AI / “New architectures for machine learning”.
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Call for project – Mathematics of deep learning

Géné-Pi
Géné-Pi
Mathematics of generative models
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MacLeOD
MacLeOD
Machine learning on geometries and distributions
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MadLearning
MadLearning
Deep Learning Mathematics: From Theory to Applications
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MAGICALL
MAGICALL
Mathematics of generative models: an interdisciplinary analysis of loss function landscapes
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PERSNET
PERSNET
PERsistent Structures in Neural NETworks
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PRODIGE-AI
PRODIGE-AI
PRObability, ranDom matrIx theory, Geometry and gEneralization for generative-AI
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TENSOR4ML
TENSOR4ML
TENSOR methods FOR mastering modern Machine Learning
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THEOREM
THEOREM
Theory for more efficient generative models
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