Machine learning takes hold in nuclear physics

Scientists have begun turning to new tools offered by machine learning to help save time and money. In the past several years, nuclear physics has seen a flurry of machine learning projects come online, with many papers published ...

Neural networks predict forces in jammed granular solids

Granular matter is all around us. Examples include sand, rice, nuts, coffee and even snow. These materials are made of solid particles that are large enough not to experience thermal fluctuations. Instead, their state is ...

Gallium oxide crystal complexity tamed by machine learning

Researchers at the University of Liverpool, the University of Bristol, University College London (UCL), and Diamond Light Source have developed new understanding of gallium oxide by combining a machine-learning theoretical ...

Using 'counterfactuals' to verify predictions of drug safety

Scientists rely increasingly on models trained with machine learning to provide solutions to complex problems. But how do we know the solutions are trustworthy when the complex algorithms the models use are not easily interrogated ...

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