Stony Brook University researchers are developing tools to predict how much energy machine-learning models consume and help ...
A dual-graph deep learning network that hard-codes petroleum physics alongside learned statistics cuts oil production prediction error to about 20 percent, far outperforming conventional models.
Researchers have developed a Michigan-style genetic fuzzy system that turns sparse multiple sclerosis records into ...
The new tool could help pinpoint the DNA changes behind hereditary diseases—a crucial step toward genetic medicines.
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