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Machine learning models via differential Geometry and Quantum theory

Objective

New machine learning advancements call for new mathematical modelling of algorithms towards interpretability and explainability. In this project we develop foundational mathematical techniques in geometric deep learning and information geometry synergically combining methods of symplectic geometry, deformation quantization and noncommutative geometry. We provide new effective geometric models for the parameter space of deep learning algorithms. We also focus on the discrete realizations of such modelling tackling Laplacians on graphs extending our investigation to graph neural networks and geometric deep learning, towards the key EU priorities of Horizon Europe.

Fields of science (EuroSciVoc)

Keywords

Programme(s)

Topic(s)

Funding Scheme

HORIZON-TMA-MSCA-SE - HORIZON TMA MSCA Staff Exchanges

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Call for proposal

(opens in new window) HORIZON-MSCA-2025-SE-01

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Coordinator

UNIVERSITA DEGLI STUDI DEL PIEMONTE ORIENTALE AMEDEO AVOGADRO
Net EU contribution
€ 60 120,00
Address
DUOMO 6
13100 Vercelli
Italy
Region
Nord-Ovest Piemonte Vercelli
Activity type
Higher or Secondary Education Establishments
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Total cost
No data

Participants (4)

Partners (3)