Nature

Deep multi-metrics learning for mobile app defect prediction using code and process metrics

The rise in mobile apps necessitates precise defect prediction to aid developers in resource allocation. The efficacy of defect prediction relies on data representation and model selection. However, ...
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Using geometry and physics to explain feature learning in deep neural networks

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
Nature

Metasurface-empowered snapshot hyperspectral imaging with convex/deep (CODE) small-data learning theory

Hyperspectral imaging is vital for material identification but traditional systems are bulky, hindering the development of compact systems. While previous metasurfaces address volume issues, the ...