About the project
There is a growing and urgent need for efficient control of generative neural networks. The goal of this project is to find new ways of controlling ML models directly using their inner or "latent" representation of the data input. The project will involve both experimental, methodological and theoretical work in order to discover general concepts for control and to better understand the inner mechanisms of these models.
Project team
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Associate Professor Benjamin Ricaud, UiT The Arctic University of Norway, Department of Physics and Technology
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Associate Professor Ali Ramezani-Kebrya, University of Oslo, Department of Informatics
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Professor Arnoldo Frigessi, University of Oslo
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PhD Fellow Daniel Kaiser, UiT The Arctic University of Norway, Department of Physics and Technology