In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively ...

A mathematics professor at The University of Manchester has developed a novel machine-learning method to detect sudden changes in fluid behaviour, improving speed and cost of identifying these ...

Methane is the second most important anthropogenic greenhouse gas after carbon dioxide, with a global warming potential roughly 28–34 times greater over a 100-year timescale. Major sources include ...

A new study published in Genome Research presents an interpretable artificial intelligence framework that improves both the accuracy and transparency of genomic prediction, a key challenge in fields ...

The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...

David J. Silvester, a mathematics professor at the University of Manchester, has developed a novel machine-learning method to ...

Proteins are the foundation of all life we currently know. With their virtually limitless diversity, they can perform a broad variety of biological functions, from delivering oxygen to cells and ...

20+ Machine Learning Methods in Groundbreaking Periodic Table From MIT, Google, Microsoft Your email has been sent A new “periodic table for machine learning” is reshaping how researchers explore AI, ...

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...

Abhirami Harilal, an Indian American applied scientist specializing in machine learning and statistical modeling for ...