Projects

Frugal AI and Embedded AI

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

Near-physics emerging models for embedded AI

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HOLIGRAIL

Hollistic approaches to greener model architectures for inference and learning

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SHARP

Sharp theoretical and algorithmic principles for frugal ML

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Trustworthy AI and Distributed AI

CAUSALI-T-AI

When causality and AI teams up to enhance interpretability and robustness of AI algorithms

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FOUNDRY

The foundations of robustness and reliability in artificial intelligence

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REDEEM

Resilient, decentralized and privacy-preserving machine learning

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SAIF

Safe AI through formal methods

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New Mathematical Foundations of 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