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Machine learning and the physics of complex and disordered systems

Project description

Machine learning could become a powerful tool in physics research

Machine learning, the study of computer algorithms that improve automatically through experience, has proven capable of solving complex engineering problems in image recognition, automated translation and gaming. It is now also being considered for applications in theoretical physics due to its ability to identify patterns in high-dimensional data and efficiently approximate complicated functional relationships. The aim of the EU-funded COMPLEX ML project is to make this relationship between machine learning and physics research stronger. Researchers will use ideas and methods from the physics of disordered systems to boost the performance and training of state-of-the-art machine learning algorithms. Furthermore, machine learning techniques will be combined with modern computational physics methods to develop new tools for disordered systems.

Coordinator

UNIVERSITAT ZURICH
Net EU contribution
€ 260 840,64
Address
Ramistrasse 71
8006 Zurich
Switzerland

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Region
Schweiz/Suisse/Svizzera Zürich Zürich
Activity type
Higher or Secondary Education Establishments
Other funding
€ 0,00

Partners (1)

Partner

Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.

THE UNIVERSITY OF CHICAGO
United States
Net EU contribution
€ 0,00
Address
S Ellis Ave 5801 Room 503
60637 Chicago Illinois

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Activity type
Higher or Secondary Education Establishments
Other funding
€ 165 265,92