Authors: George Rajna
Electrical engineers at Duke University have harnessed the power of machine learning to design dielectric (non-metal) metamaterials that absorb and emit specific frequencies of terahertz radiation.  Understanding how a robot will react under different conditions is essential to guaranteeing its safe operation.  Marculescu, along with ECE Ph.D. student Chieh Lo, has developed a machine learning algorithm-called MPLasso-that uses data to infer associations and interactions between microbes in the GI microbiome.  A team of researchers from the University of Muenster in Germany has now demonstrated that this combination is extremely well suited to planning chemical syntheses-so-called retrosyntheses-with unprecedented efficiency.  Two physicists at ETH Zurich and the Hebrew University of Jerusalem have developed a novel machine-learning algorithm that analyses large data sets describing a physical system and extract from them the essential information needed to understand the underlying physics. 
Comments: 34 Pages.
[v1] 2019-09-28 03:26:09
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