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.
Fields of science
- natural sciencescomputer and information sciencesartificial intelligencemachine learningreinforcement learning
- natural sciencesphysical sciencestheoretical physics
- natural sciencescomputer and information sciencesartificial intelligencecomputational intelligence
- humanitiesphilosophy, ethics and religionphilosophy
Funding SchemeMSCA-IF-GF - Global Fellowships
Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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