Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...
A recent study published in Scientific Reports highlights the potential of PyCaret, an automated machine learning (ML) platform, in developing and evaluating predictive models for the compressive ...
HighlightsConfirmation of Adelita as a large porphyry-skarn mineral system with vertically extensive feeder structuresIdentification of 32 priority exploration targets (18 targets via combination of ...
The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...
As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...
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