About the project
Machine learning increasingly needs to deal with new types of data, needs new ways to incorporate a priori knowledge for better generalization and explainability, and needs to discover causal relationships. A key research question for this project is: How do we develop novel measures of discrepancy or divergence to best capture information in data for efficient neural networks learning?
Project team
- Professor Robert Jenssen, UiT The Arctic University of Norway, Department of Physics and Technology
Associate Professor Shujian Yu, UiT The Arctic University of Norway, Department of Physics and Technology
Associate Professor Johan Pensar, University of Oslo, Department of Mathematics
Associate Professor Ali Ramezani-Kebrya, University of Oslo, Department of Informatics
Professor Sylvia Richardson, University of Cambridge, MRC Biostatistics Unit