A team has proposed an interpretable machine learning approach that predicts print time and filament use for FFF, potentially ...

Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

Mentalising brain signatures reveal distinct self/other neural patterns from adolescence and are altered in schizophrenia, suggesting candidate neuromarkers.

Further simulations show that machine learning models can automatically capture non-additive effects and multi-locus interactions without explicitly specifying interaction terms, thereby improving the ...

On the 31st of May 2024, M.Sc. Anton Björklund defends his PhD thesis on Interpretable and explainable machine learning for natural sciences. The thesis is related to research done in the Department ...

A fast and accurate surrogate model screens over 10,000 possible metal-oxide supports for a platinum nanocatalyst to prevent sintering under high temperatures. Metal nanoparticles catalyze reactions ...

Machine learning is a powerful tool in computational biology, enabling the analysis of a wide range of biomedical data such as genomic sequences and biological imaging. But when researchers use ...

Artificial intelligence is currently controlled by a number of tech giants in the United States and China. But Europe can ...